Google X - secret Research Lab of Google.
Thursday, December 15, 2011
Wednesday, December 14, 2011
Productivity Future Vision (2011)
Excellent video that depicts the future and also the main technologies that will be the upcoming trends:
- Visualization with Hi-Res Display
- Touch Screens and Voice Recognition (just like what Apple have done their "touch" iPhones and voice "Siri")
- Intelligent (profile based)
- Ubiquitous communications (broadband wireless)
- Multiple devices (seamless switching and sharing of contents)
Sunday, December 11, 2011
Wireless Watch: Wi-Fi takes its place at the heart of carriers’ data strategies, looking beyond offload by Rethink Research
Wireless Watch: Wi-Fi takes its place at the heart of carriers’ data strategies, looking beyond offload
Nov 16, 2011 – Rethink Research
The enthusiasm with which mobile operators have embraced data offload to Wi-Fi, as a way to ease the strain on their creaking 3G networks, often obscures the fact that what they are doing remains, for now, highly unsophisticated. Some cellcos have invested large sums in building their own hotspot networks, or connecting to those of partners, but beyond the clear benefit of getting traffic off the cellular system, they are not getting much return. The user experience remains clumsy, without seamless hand-off between 3G and WLan nodes; the hotspots are not usually scientifically planned to mirror the areas of most traffic; operators cannot track user behaviour once the customer has been offloaded, and so lose the chance to monetize; and the link to the unlicensed network may not even be fully secure.
All these weaknesses indicate the haste with which panicking cellcos rushed to adopt offload strategies, but also the fact that most of them initially regarded Wi-Fi as a short to medium term stopgap, before the happy days when their data burdens would be lifted by the combination of LTE and HSPA+ upgrades, and offload to the far more controllable femtocells. Now, however, as operators start to roll out the air interface upgrades and the femtos, they are quickly realizing that, while both those strategies will be very helpful in meeting exploding mobile data demands, they will not be enough in themselves. Introducing LTE will, on average, quadruple data capacity, says Cisco, but most cellcos in developed economies will see their capacity requirement go up by 32 times by 2015.
Against such a backdrop, it is clear that carriers will have to harness any piece of technology and spectrum they can grasp, and that will mean keeping Wi-Fi permanently in the mix. And if the platform is to be a long term fixture, it will need to be approached more strategically, and with greater thought for how to maximize its benefits both to customers and the carrier itself. Operators are starting to think beyond simple offload, and think in terms of bringing Wi-Fi access points into the future ‘HetNet’ (heterogeneous network), which will boost capacity and coverage by integrating multiple air interfaces, cell sizes and spectrum bands. In a new survey of over 100 mobile operators, Rethink Technology Research studied the ways in which carriers will plan their future access networks in order to meet the needs of the data boom. The respondents identified five key weapons, most of them complementary – in the near term, Wi-Fi offload, small self-organizing cells, and more sophisticated traffic management tools; and a few years out, the extension of those trends into HetNets and LTE-Advanced upgrades.
For deployments in 2011-2013, over half of carriers rate offload as one of their top two weapons against the data deluge, followed closely by the move towards smaller, self-organizing cells, and 46% are also heavily focused on traffic management. Only 4% see LTE-Advanced as a top priority in this timeframe, but for 2014-2015, the standards upgrade leaps becomes a key strategic factor for 30% of respondents. LTE-A supports HetNets in a more standardized way and should spur their adoption, and indeed, for the second wave, over one-quarter of cellcos see HetNets as one of their top two weapons, while simple offload has dropped back to 20%.
The findings show that carriers will move from their unsophisticated use of Wi-Fi towards a more complex and carefully planned strategy which relies on WLans, indoor femtocells and public access metrocells to supplement or even replace the traditional cellular network.
But for carrier Wi-Fi to take this enhanced role, the holes currently existing in the platform need to be filled rapidly, a process which will throw up some key opportunities for companies with expertise in critical areas - metrozones, cross-platform billing and hand-off, security, interference management, and traffic prioritization. Obvious giants are already staking their claim, from Cisco to Nokia Siemens, but some of the more interesting moves are seen coming from the smaller players as the worlds of Wi-Fi offload, small cells and intelligent traffic management collide, and as operators start to demand that their WLans are intelligent, secure and fully integrated with their 3G and 4G systems.
Among these independents are two stalwarts of the Wi-Fi market, Ruckus Wireless and BelAir Networks, which are now looking to expand their remit deep into the heart of the cellcos’ networks and carve out a position there ahead of the expected HetNet boom. Ruckus has its roots in the indoor market, particularly video-over-WLan systems, and learned how to deal with carriers in that space.
Last year it ventured outdoors with metrozone products and scored its flagship offload contract with Japan’s KDDI Wireless, which recently announced “the world’s first and largest ‘instant-on’ Wi-Fi access and mobile data offload service”. It is using Ruckus access points and controllers to build a hotspot network which will reach 100,000 locations by next March, supporting seamless hand-off from 3G and free Wi-Fi for data customers. As the GigaOM blog pointed out, “100,000 access points will give KDDI a Wi-Fi node for every 320 customers. AT&T has a Wi-Fi access node for every 4063 customers. The sheer density of KDDI’s deployment assures that Wi-Fi will become a major component of its mobile data networking strategy, rather than a mere supplementary technology.”
Meanwhile, BelAir has major offload deals with AT&T and several US cablecos, including Cablevision, the poster child for using Wi-Fi instead of cellular MVNO deals to add a wireless element to a cable triple play. Cable operators are a key target market for the carrier Wi-Fi brigade, since they have no vested interest in 3G solutions (even the most 3G-oriented of the US players, Cox Communications, pulled out of offering mobile services this month because of the costs and poor returns).
But BelAir is looking well beyond simple offload, and indeed, no longer likes to be known as a Wi-Fi firm, because it is supporting LTE too in its latest small cell platform, the 2100, designed to be a component of a flexibly planned HetNet. Drawing on a decade in the Wi-Fi metro space, it is now focusing on metrozones in their newer incarnation – carrier-controlled, running a mixture of Wi-Fi and cellular small cells, and hugely scalable. A couple of months after unveiling the 2100, which has integrated backhaul as well as multimode support, the vendor is moving further into the heart of the carrier network with its GigXone offering. This consists of a set of Wi-Fi controllers and access points, which can scale metro networks to hundreds of thousands of nodes.
CMO Ronny Haraldsvik says a commercial deployment of 100,000 nodes is “not very far away”, and in future such zones will take Wi-Fi from a “stopgap solution” to a permanent part of the network strategy, he argues. This will be driven by the emergence of products which make Wi-Fi truly carrier class – a category where he currently places only BelAir, Cisco and Ruckus – and also by standards work, particularly around HetNets in LTE+, integration of APs with femtocells, and in the Hotspot 2.0 initiative. The latter will use the upcoming 802.11u standard extension, for roaming with 3G, and there will be a Wi-Fi Alliance certification program from 2012, for a set of seamless roaming and authentication standards.
Not only does BelAir hope to be part of carriers’ offload and HetNet strategies with beefed-up capacity and multimode support, but it believes it is time for operators to think more closely about monetizing their Wi-Fi connections and think of new business models. The GigXone not only enables more than enough capacity to support mobile data needs, but it supports virtualized access points, so that cellcos can sell the excess to third parties.
Several cellcos round the world are enhancing their brand awareness and business model by offering Wi-Fi access services outside their own customer bases – even, in the case of O2 UK, for free. GigXone not only works with existing 3GPP billing systems, but via virtualization, can enable up to eight virtual Lans, which can offer hosted services to the third party partners or to private customers such as enterprises. Virtual small cells enable each SSID to be independently configured to connect to different carrier core networks. Security, mobility, AAA and DHCP parameters can also be set on a per-SSID basis.
“Building a small cell network once and leveraging it many more times is nirvana for carriers and their investors in these capex strained times,” said Haraldsvik, and BelAir CEO Bernard Herscovich added in a statement: “Small cells are not just about 3G offload anymore as our carrier customers want to offer a reliable brand experience throughout their network service areas, regardless of radio access technologies. Mobile and cable carrier customers asked us to build a highly scalable system well suited for indoor and outdoor, business and consumers, with multimode small cell options for licensed and unlicensed, and that’s what we did with GigXone.”
The products contained within GigXone include the multimode small cells themselves as well as Carrier Cloud and HotZone controllers. There are five new elements. The Carrier Cloud Controller (BelAirCC8000) can support 500 access points and, with the BelView software, can scale to 100,000 cells with the controller managing wide area mobility via Mobile IP, L2VPN or GRE tunnels. The HotZone Controller (BelAirHZ4000) is a smaller, premises based system for ad hoc deployments such as convention centers, or for enterprises and smaller zones. The cells themselves are the BelAir 1000, the entry level model for indoor locations; the BelAir 1100 for campus networks or events; and the BelAir3200, a strand‐mounted product for cablecos with integrated DOCSIS 3.0 cable modem.
Cisco is also addressing the walls that still exist between the cellco’s 3G and Wi-Fi networks. Earlier this year, it introduced the Next Generation Hotspot system for its Aironet 1550 access points, a platform for authentication and roaming. "We are positioning this as a peaceful coexistence with 4G. Both have a role," said Jaishree Subramania, product marketing manager for mobility. “The very foundation of our approach is a carrier grade system across the entire network architecture. The key is the unification for architecture. It's all about delivering consistent Wi-Fi experience across a variety of environments, and all of this can be managed and controlled from a single point in a carrier network." The architecture will also support 802.11u, which allows Wi-Fi APs to advertise themselves and devices to connect to them using SIM-based authentication, without the user having to select an SSID number. Cisco is also thinking in terms of enabling new revenue streams for operators, saying 11u will “pave the way for new service delivery”, such as retailers offering instant coupons to people coming into their stores. Such applications would harness not just 11u but the Mobility Services Advertisement Protocol (MSAP), which allows 11u devices to obtain local information as they authenticate. "802.11u might be able to advertise that there are services available, while MSAP is the protocol that get the service into an app to be delivered down to a device," Cisco said.
Improved roaming, hand-off, authentication and services could all make Wi-Fi a more strategic part of the cellco’s network, but all that could come to grief if the connections are not fully secure. This has been a neglected risk, according to network infrastructure vendor Radisys, which took a position in the offload and data management markets when it acquired Continuous Computing. It promises to secure the ‘offload link’ between the 3G system and the WLan, using standards-based technology rather than expensive proprietary solutions.
Currently, the firm says, carriers are often leaving that link in their data chain poorly secured, or they are spending large sums on customized solutions. The upgraded SEG-100 security gateway, by contrast, supports standards like I-WLan (Interworking Wireless Lan), and the 3GPP specification, TTG (Tunnel Terminating Gateway).
Without a dedicated offload solution from such as a TTG platform, the connection between the carrier’s network and the WLan is often “untrusted” and insecure, warns Radisys. “Carriers are looking for highly scalable and cost effective solutions to protect networks and mobile traffic,” said senior product line manager Jeff Sharpe. “Compared to enterprise class security offerings, the SEG-100 is a carrier class solution that supports an industry-best 200,000 concurrent, bidirectional IPSec tunnels running at speeds greater than 10Gbps on a stateful, high availability system, thus enabling lowest cost per subscriber.”
Manish Singh, CTO at Radisys, told TotalTelecom that backhaul was another potential security risk, which the SEG-100 could help address. Moving traffic to third party backhaul systems was “creating a security hole, and you need to plug it,” he said. "If the weakest link is the backhaul then the hackers will target that.” The issues arise when cellcos address the strain on their backhaul links by leasing additional capacity from third parties, or by offloading. Any transfer between different networks, especially those out of the carrier’s control, can open up vulnerabilities.
The company claims that the SEG-100 is the only turnkey TTG and I-WLan solution which can be integrated automatically into any chassis or network supporting the ATCA standard. This is because it comes as an ATCA blade rather than a standalone box, reducing deployment time and cost within existing networks.
Despite all these enhancements to make WLans truly carrier-class, most operators will still see Wi-Fi as something of a second string, keeping their licensed spectrum, 3GPP crown jewels at the heart of the strategy. But we should not forget the new service providers (and even some old ones) which will look for competitive advantage by placing Wi-Fi at the center of their business models – from China Mobile with its Wi-Fi iPhone strategy and O2 with its free hotspots for all, to US newcomer Republic Wireless, which has a highly WLan-centric offering.
The firm has launched a hybrid Wi-Fi/cellular service for Android smartphones which manages to achieve the rockbottom price of $19 a month for unlimited use, providing most of that is over Wi-Fi - focusing on ‘mobile onload’ rather than Wi-Fi offload. The proposition is interesting because it is not entirely about Wi-Fi, like the China Mobile iPhone, or Google’s dreams of a metrozone which elbows out cellco offerings. Instead, it takes what TelecomTV calls a ‘cell light' approach. The plan incentivizes the user to connect via Wi-Fi wherever possible – at home, hotspot or work – by imposing strict caps on cellular usage, and by supporting a transparent and fully integrated voice/text experience over the WLan (in both directions). For $19, the user gets unlimited Wi-Fi calls, text and data, but is limited to 400 minutes, 200 texts and 600Mbytes of data on the cellular system. Customers can monitor whether they are on Wi-Fi, and their cellular usage, using an on-board app. If they persistently overuse their mobile allowances, they can face possible account termination.
Whether or not Republic succeeds in the tough US market, it is an example of how carriers are starting to think creatively about how they can harness Wi-Fi for more than offload, and to be a permanent element in their data strategies, and new business models, well into the LTE-Advanced era.
Courtesy Rethink Research.
Nov 16, 2011 – Rethink Research
The enthusiasm with which mobile operators have embraced data offload to Wi-Fi, as a way to ease the strain on their creaking 3G networks, often obscures the fact that what they are doing remains, for now, highly unsophisticated. Some cellcos have invested large sums in building their own hotspot networks, or connecting to those of partners, but beyond the clear benefit of getting traffic off the cellular system, they are not getting much return. The user experience remains clumsy, without seamless hand-off between 3G and WLan nodes; the hotspots are not usually scientifically planned to mirror the areas of most traffic; operators cannot track user behaviour once the customer has been offloaded, and so lose the chance to monetize; and the link to the unlicensed network may not even be fully secure.
All these weaknesses indicate the haste with which panicking cellcos rushed to adopt offload strategies, but also the fact that most of them initially regarded Wi-Fi as a short to medium term stopgap, before the happy days when their data burdens would be lifted by the combination of LTE and HSPA+ upgrades, and offload to the far more controllable femtocells. Now, however, as operators start to roll out the air interface upgrades and the femtos, they are quickly realizing that, while both those strategies will be very helpful in meeting exploding mobile data demands, they will not be enough in themselves. Introducing LTE will, on average, quadruple data capacity, says Cisco, but most cellcos in developed economies will see their capacity requirement go up by 32 times by 2015.
Against such a backdrop, it is clear that carriers will have to harness any piece of technology and spectrum they can grasp, and that will mean keeping Wi-Fi permanently in the mix. And if the platform is to be a long term fixture, it will need to be approached more strategically, and with greater thought for how to maximize its benefits both to customers and the carrier itself. Operators are starting to think beyond simple offload, and think in terms of bringing Wi-Fi access points into the future ‘HetNet’ (heterogeneous network), which will boost capacity and coverage by integrating multiple air interfaces, cell sizes and spectrum bands. In a new survey of over 100 mobile operators, Rethink Technology Research studied the ways in which carriers will plan their future access networks in order to meet the needs of the data boom. The respondents identified five key weapons, most of them complementary – in the near term, Wi-Fi offload, small self-organizing cells, and more sophisticated traffic management tools; and a few years out, the extension of those trends into HetNets and LTE-Advanced upgrades.
For deployments in 2011-2013, over half of carriers rate offload as one of their top two weapons against the data deluge, followed closely by the move towards smaller, self-organizing cells, and 46% are also heavily focused on traffic management. Only 4% see LTE-Advanced as a top priority in this timeframe, but for 2014-2015, the standards upgrade leaps becomes a key strategic factor for 30% of respondents. LTE-A supports HetNets in a more standardized way and should spur their adoption, and indeed, for the second wave, over one-quarter of cellcos see HetNets as one of their top two weapons, while simple offload has dropped back to 20%.
The findings show that carriers will move from their unsophisticated use of Wi-Fi towards a more complex and carefully planned strategy which relies on WLans, indoor femtocells and public access metrocells to supplement or even replace the traditional cellular network.
But for carrier Wi-Fi to take this enhanced role, the holes currently existing in the platform need to be filled rapidly, a process which will throw up some key opportunities for companies with expertise in critical areas - metrozones, cross-platform billing and hand-off, security, interference management, and traffic prioritization. Obvious giants are already staking their claim, from Cisco to Nokia Siemens, but some of the more interesting moves are seen coming from the smaller players as the worlds of Wi-Fi offload, small cells and intelligent traffic management collide, and as operators start to demand that their WLans are intelligent, secure and fully integrated with their 3G and 4G systems.
Among these independents are two stalwarts of the Wi-Fi market, Ruckus Wireless and BelAir Networks, which are now looking to expand their remit deep into the heart of the cellcos’ networks and carve out a position there ahead of the expected HetNet boom. Ruckus has its roots in the indoor market, particularly video-over-WLan systems, and learned how to deal with carriers in that space.
Last year it ventured outdoors with metrozone products and scored its flagship offload contract with Japan’s KDDI Wireless, which recently announced “the world’s first and largest ‘instant-on’ Wi-Fi access and mobile data offload service”. It is using Ruckus access points and controllers to build a hotspot network which will reach 100,000 locations by next March, supporting seamless hand-off from 3G and free Wi-Fi for data customers. As the GigaOM blog pointed out, “100,000 access points will give KDDI a Wi-Fi node for every 320 customers. AT&T has a Wi-Fi access node for every 4063 customers. The sheer density of KDDI’s deployment assures that Wi-Fi will become a major component of its mobile data networking strategy, rather than a mere supplementary technology.”
Meanwhile, BelAir has major offload deals with AT&T and several US cablecos, including Cablevision, the poster child for using Wi-Fi instead of cellular MVNO deals to add a wireless element to a cable triple play. Cable operators are a key target market for the carrier Wi-Fi brigade, since they have no vested interest in 3G solutions (even the most 3G-oriented of the US players, Cox Communications, pulled out of offering mobile services this month because of the costs and poor returns).
But BelAir is looking well beyond simple offload, and indeed, no longer likes to be known as a Wi-Fi firm, because it is supporting LTE too in its latest small cell platform, the 2100, designed to be a component of a flexibly planned HetNet. Drawing on a decade in the Wi-Fi metro space, it is now focusing on metrozones in their newer incarnation – carrier-controlled, running a mixture of Wi-Fi and cellular small cells, and hugely scalable. A couple of months after unveiling the 2100, which has integrated backhaul as well as multimode support, the vendor is moving further into the heart of the carrier network with its GigXone offering. This consists of a set of Wi-Fi controllers and access points, which can scale metro networks to hundreds of thousands of nodes.
CMO Ronny Haraldsvik says a commercial deployment of 100,000 nodes is “not very far away”, and in future such zones will take Wi-Fi from a “stopgap solution” to a permanent part of the network strategy, he argues. This will be driven by the emergence of products which make Wi-Fi truly carrier class – a category where he currently places only BelAir, Cisco and Ruckus – and also by standards work, particularly around HetNets in LTE+, integration of APs with femtocells, and in the Hotspot 2.0 initiative. The latter will use the upcoming 802.11u standard extension, for roaming with 3G, and there will be a Wi-Fi Alliance certification program from 2012, for a set of seamless roaming and authentication standards.
Not only does BelAir hope to be part of carriers’ offload and HetNet strategies with beefed-up capacity and multimode support, but it believes it is time for operators to think more closely about monetizing their Wi-Fi connections and think of new business models. The GigXone not only enables more than enough capacity to support mobile data needs, but it supports virtualized access points, so that cellcos can sell the excess to third parties.
Several cellcos round the world are enhancing their brand awareness and business model by offering Wi-Fi access services outside their own customer bases – even, in the case of O2 UK, for free. GigXone not only works with existing 3GPP billing systems, but via virtualization, can enable up to eight virtual Lans, which can offer hosted services to the third party partners or to private customers such as enterprises. Virtual small cells enable each SSID to be independently configured to connect to different carrier core networks. Security, mobility, AAA and DHCP parameters can also be set on a per-SSID basis.
“Building a small cell network once and leveraging it many more times is nirvana for carriers and their investors in these capex strained times,” said Haraldsvik, and BelAir CEO Bernard Herscovich added in a statement: “Small cells are not just about 3G offload anymore as our carrier customers want to offer a reliable brand experience throughout their network service areas, regardless of radio access technologies. Mobile and cable carrier customers asked us to build a highly scalable system well suited for indoor and outdoor, business and consumers, with multimode small cell options for licensed and unlicensed, and that’s what we did with GigXone.”
The products contained within GigXone include the multimode small cells themselves as well as Carrier Cloud and HotZone controllers. There are five new elements. The Carrier Cloud Controller (BelAirCC8000) can support 500 access points and, with the BelView software, can scale to 100,000 cells with the controller managing wide area mobility via Mobile IP, L2VPN or GRE tunnels. The HotZone Controller (BelAirHZ4000) is a smaller, premises based system for ad hoc deployments such as convention centers, or for enterprises and smaller zones. The cells themselves are the BelAir 1000, the entry level model for indoor locations; the BelAir 1100 for campus networks or events; and the BelAir3200, a strand‐mounted product for cablecos with integrated DOCSIS 3.0 cable modem.
Cisco is also addressing the walls that still exist between the cellco’s 3G and Wi-Fi networks. Earlier this year, it introduced the Next Generation Hotspot system for its Aironet 1550 access points, a platform for authentication and roaming. "We are positioning this as a peaceful coexistence with 4G. Both have a role," said Jaishree Subramania, product marketing manager for mobility. “The very foundation of our approach is a carrier grade system across the entire network architecture. The key is the unification for architecture. It's all about delivering consistent Wi-Fi experience across a variety of environments, and all of this can be managed and controlled from a single point in a carrier network." The architecture will also support 802.11u, which allows Wi-Fi APs to advertise themselves and devices to connect to them using SIM-based authentication, without the user having to select an SSID number. Cisco is also thinking in terms of enabling new revenue streams for operators, saying 11u will “pave the way for new service delivery”, such as retailers offering instant coupons to people coming into their stores. Such applications would harness not just 11u but the Mobility Services Advertisement Protocol (MSAP), which allows 11u devices to obtain local information as they authenticate. "802.11u might be able to advertise that there are services available, while MSAP is the protocol that get the service into an app to be delivered down to a device," Cisco said.
Improved roaming, hand-off, authentication and services could all make Wi-Fi a more strategic part of the cellco’s network, but all that could come to grief if the connections are not fully secure. This has been a neglected risk, according to network infrastructure vendor Radisys, which took a position in the offload and data management markets when it acquired Continuous Computing. It promises to secure the ‘offload link’ between the 3G system and the WLan, using standards-based technology rather than expensive proprietary solutions.
Currently, the firm says, carriers are often leaving that link in their data chain poorly secured, or they are spending large sums on customized solutions. The upgraded SEG-100 security gateway, by contrast, supports standards like I-WLan (Interworking Wireless Lan), and the 3GPP specification, TTG (Tunnel Terminating Gateway).
Without a dedicated offload solution from such as a TTG platform, the connection between the carrier’s network and the WLan is often “untrusted” and insecure, warns Radisys. “Carriers are looking for highly scalable and cost effective solutions to protect networks and mobile traffic,” said senior product line manager Jeff Sharpe. “Compared to enterprise class security offerings, the SEG-100 is a carrier class solution that supports an industry-best 200,000 concurrent, bidirectional IPSec tunnels running at speeds greater than 10Gbps on a stateful, high availability system, thus enabling lowest cost per subscriber.”
Manish Singh, CTO at Radisys, told TotalTelecom that backhaul was another potential security risk, which the SEG-100 could help address. Moving traffic to third party backhaul systems was “creating a security hole, and you need to plug it,” he said. "If the weakest link is the backhaul then the hackers will target that.” The issues arise when cellcos address the strain on their backhaul links by leasing additional capacity from third parties, or by offloading. Any transfer between different networks, especially those out of the carrier’s control, can open up vulnerabilities.
The company claims that the SEG-100 is the only turnkey TTG and I-WLan solution which can be integrated automatically into any chassis or network supporting the ATCA standard. This is because it comes as an ATCA blade rather than a standalone box, reducing deployment time and cost within existing networks.
Despite all these enhancements to make WLans truly carrier-class, most operators will still see Wi-Fi as something of a second string, keeping their licensed spectrum, 3GPP crown jewels at the heart of the strategy. But we should not forget the new service providers (and even some old ones) which will look for competitive advantage by placing Wi-Fi at the center of their business models – from China Mobile with its Wi-Fi iPhone strategy and O2 with its free hotspots for all, to US newcomer Republic Wireless, which has a highly WLan-centric offering.
The firm has launched a hybrid Wi-Fi/cellular service for Android smartphones which manages to achieve the rockbottom price of $19 a month for unlimited use, providing most of that is over Wi-Fi - focusing on ‘mobile onload’ rather than Wi-Fi offload. The proposition is interesting because it is not entirely about Wi-Fi, like the China Mobile iPhone, or Google’s dreams of a metrozone which elbows out cellco offerings. Instead, it takes what TelecomTV calls a ‘cell light' approach. The plan incentivizes the user to connect via Wi-Fi wherever possible – at home, hotspot or work – by imposing strict caps on cellular usage, and by supporting a transparent and fully integrated voice/text experience over the WLan (in both directions). For $19, the user gets unlimited Wi-Fi calls, text and data, but is limited to 400 minutes, 200 texts and 600Mbytes of data on the cellular system. Customers can monitor whether they are on Wi-Fi, and their cellular usage, using an on-board app. If they persistently overuse their mobile allowances, they can face possible account termination.
Whether or not Republic succeeds in the tough US market, it is an example of how carriers are starting to think creatively about how they can harness Wi-Fi for more than offload, and to be a permanent element in their data strategies, and new business models, well into the LTE-Advanced era.
Courtesy Rethink Research.
Friday, November 25, 2011
Wednesday, October 19, 2011
Meet the Swarm Lab and AMPLab (Berkeley)
Two labs, two high-impact missions By Abby Cohn BIG DATA, BIG CHALLENGES: What to do about the massive aggregation of digital data? For researchers at the AMPLab, the challenge is not just finding ways to store it all, but also developing tools that will efficiently manage and analyze this information, thus maximizing its value. LUIS M. MOLINA Two new research ventures at Berkeley Engineering have boundary-shattering visions for the future of computing. Meet the Swarm Lab and AMPLab. Jointly unveiled at the recent Berkeley EECS Annual Research Symposium (BEARS), the labs have distinct missions. The Swarm Lab will advance work in tiny wireless sensors capable of linking our homes, cities and bodies to the cyber world. The AMPLab will focus on solutions to the growing challenge of storing, accessing and analyzing a deluge of data that has begun overwhelming today’s technology. Each is assembling an interdisciplinary team composed of leading computer scientists from multiple specialties. “You really need expertise across a wide spectrum of the computer landscape,” says Michael J. Franklin, professor of computer science and director of the AMPLab, whose initials stand for algorithms, machines and people. Housed in Soda Hall, the AMPLab is creating cutting-edge tools to manage and extract valuable information from the plethora of data being collected digitally. Its mission comes in response to the phenomenon known as “big data” or the “data deluge”: Modern computing is gathering so much information—ranging from online mouse clicks to human genome sequencing to telescope imagery of the universe—that it lacks the ability to store it, let alone analyze it to understand trends or make predictions. “It used to be that you had to be a big phone company or bank to have a data problem,” says Franklin. “Now everyone is starting to collect more data than they can make sense of.” The AMPLab is tackling those challenges by taking a three-pronged approach. Researchers plan to improve the efficiency and quality of machine learning (algorithms), scale up datacenters (machines) and leverage the input of human intelligence and activities through crowdsourcing (people). Instead of advancing each dimension independently, the lab will work to integrate the three into a unified system. “We have world-class people in all dimensions,” Franklin says. “We’re taking a holistic view of the system architecture.” Illustrating the value that can be mined from massive collections of information, the AMPLab is already teaming with several real-world projects using big data to create personalized genomics information, crowd-based public opinion forums and urban development simulations. Another early participant is the Mobile Millennium project. Headed by Alex Bayen, associate professor of civil and environmental engineering, that endeavor is creating a real-time traffic monitoring system by processing millions of data points daily from GPS-enabled cell phones and road sensors. The AMPLab is supported by Google, SAP and some 10 other corporate sponsors. The lab is expected to run for five years. ABUZZ WITH POSSIBLILITIES: Among other projects, researchers at the Swarm Lab will develop flexible, paper-like and wearable materials from innovative components, such as a UC Berkeley research team’s artificial e-skin made of nanowires, pictured above. COURTESY ALI JAVEY AND KUNIHARU TAKEI Meanwhile, construction of the Swarm Lab, which will occupy the entire fourth floor of Cory Hall, is expected to start soon. Launched with major support from Qualcomm Inc., the lab will explore and develop smart sensor networks that can be embedded in walls, streets and even the human body. These trillions of tiny, wireless sensors—collectively known as “the swarm”—will capture information about ourselves and our world and provide new ways of interacting, says Jan Rabaey, professor of electrical engineering and computer sciences. He hopes to open the Swarm Lab by the end of this year. The lab will serve as an incubator for swarm applications and platforms. Potential applications for the technology include systems that monitor environmental conditions, energy use and personal health. Down the road, swarms could augment reality by creating 3D simulations complete with such sensory experiences as touch, sound and smell. If, for instance, a harmful chemical starts leaking from a local oil refinery, the wireless network of the future could notify nearby residents with a message that pops up on their bathroom mirrors. Or sensors in the human body might provide instant cholesterol readings or constant EKG monitorings for patients with heart problems. In the future of e-commerce, shoppers could try on clothes virtually and get sensory feedback if the shoes they’re considering will pinch their toes. Rabaey believes ubiquitous sensory swarms will become a reality within the next 20 years as today’s pad devices “disappear and fade away in the walls or our body.” The biggest hurdle to that vision is the anticipated public concern about privacy, health and other issues related to embedded sensors, he says. Rabaey is confident those worries can be overcome with such measures as careful privacy controls and public education. He equates the potential of sensory swarms to that of mobile devices when they first debuted. “I believe it’s really going to revolutionize how we interact with the world and how we’re going to interact with each other,” he says. [SOURCE: HERE] |
Monday, October 17, 2011
The Perks of Working at Google, Facebook, Twitter and More [INFOGRAPHIC]
[SOURCE: Mashable]
Are you a techie looking for work? We recently offered some tips on landing jobs at Google, Apple and Facebook, but there are more companies in the Valley than those three. And you might be wondering what the culture is like at each of these companies, as well as at LinkedIn, Twitter, Eventbrite, Gaia and Tagged.
Back in August, we brought you word of awesome perks at various startups; now, we bring you perks at a number of Silicon Valley’s largest and finest. From yoga to catered lunches, 401(k)s to dry cleaning, sports teams to vacation days, these tech companies seem to understand that quality of life affects productivity — and that having to run fewer errands after work means you’re more likely to stay at the office.
Check out the infographic below from ResumeBear for a breakdown of who offers what perks. Do you work at any of these companies and take advantage of any of these perks? Let us know in the comments below.
Are you a techie looking for work? We recently offered some tips on landing jobs at Google, Apple and Facebook, but there are more companies in the Valley than those three. And you might be wondering what the culture is like at each of these companies, as well as at LinkedIn, Twitter, Eventbrite, Gaia and Tagged.
Back in August, we brought you word of awesome perks at various startups; now, we bring you perks at a number of Silicon Valley’s largest and finest. From yoga to catered lunches, 401(k)s to dry cleaning, sports teams to vacation days, these tech companies seem to understand that quality of life affects productivity — and that having to run fewer errands after work means you’re more likely to stay at the office.
Check out the infographic below from ResumeBear for a breakdown of who offers what perks. Do you work at any of these companies and take advantage of any of these perks? Let us know in the comments below.
Sunday, October 16, 2011
Socialnets Resources
[1] | S. Tang, E. Jaho, I. Stavrakakis, I. Koukoutsidis, and P. Van Mieghem. Modeling gossip-based content dissemination and search in distributed p2p overlays. Computer Communications, 34(6):765-779, May 2011. [ bib ] |
[2] | E. Jaho, M. Karaliopoulos, and I. Stavrakakis. ISCoDe: a framework for interest similarity-based community detection in social networks. In Third International Workshop on Network Science for Communication Networks (INFOCOM-NetSciCom'11), Shanghai, China, 15 April 2011. [ bib ] |
[3] | Eleonora Borgia, Marco Conti, and Andrea Passarella. Autonomic detection of dynamic social communities in opportunistic networks. In MedHocNet 2011 (submitted), 2011. [ bib ] |
[4] | Marco Conti, Andrea Passarella, and Fabio Pezzoni. A model for the generation of social network graphs. In IEEE AOC 2011, 2011. [ bib ] |
[5] | Daniele Vilone and Andrea Guazzini. Social aggregation as a cooperative game. Physica A, ((to appear)), 2011. [ bib ] |
[6] | Ioannis Stavrakakis. Some distributed approaches to the service facility location problem in dynamic and complex networks. In My T. Thai and Panos Pardalos, editors, Handbook of Optimization in Complex Networks: Vol. 1 (Theory and Applications) and Vol. 2 (Communication and Social Networks). Springer, summer 2011. [ bib ] |
[7] | S.M. Allen, M.J. Chorley, G.B. Colombo, E. Jaho, M. Karaliopoulos, I. Stavrakakis, and R.M. Whitaker. Exploiting user interest similarity and social links for micro-blog forwarding in mobile opportunistic networks. Pervasive and Mobile Computing, ((submitted)), 2011. [ bib ] |
[8] | E. Jaho, I. Koukoutsidis, I. Stavrakakis, and I. Jaho. Cooperative content replication in networks with autonomic nodes. to IEEE Journal on Selected Areas in Communications - Special Issue Cooperative Networking Challenges and Applications, ((submitted)), 2011. [ bib ] |
[9] | Ioannis Stavrakakis. Relevance and cognition for pervasive computation at scale. In NSF Workshop on Pervasive Computing at Scale (PeCS). Univ. of Washington, Seattle, USA, January 2011. [ bib | .pdf ] |
[10] | R. Dunbar and A. Sutcliffe. Social complexity and intelligence. In J. Vonk and T. Shackleford, editors, Oxford Handbook of Comparative Evolutionary Psychology. Oxford University Press, 2011. [ bib ] |
[11] | R.I.M. Dunbar. Evolutionary basis of the social brain. In J. Decety and J. Cacioppo, editors, Oxford Handbook of Social Neuroscience, pages 28-28. Oxford University Press, 2011. [ bib ] |
[12] | M.N. Burton-Chellew and R.I.M. Dunbar. Close relationships: impact of romantic relationships and kinship. Social Psychology, ((submitted)), 2011. [ bib ] |
[13] | A. Sutcliffe, R.I.M. Dunbar, J. Binder, and H. Arrow. Relationships and the social brain: integrating psychological and evolutionary perspectives. British Journal of Psychology, ((in press)), 2011. [ bib ] |
[14] | T. V. Pollett, S. Roberts, and Robin I. M. Dunbar. Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members. Cyberpsychology, Behavior and Social Networking, ((in press)), 2011. [ bib ] |
[15] | T. V. Pollett, S. Roberts, and Robin I. M. Dunbar. Extraverts have larger social network layers but do not feel emotionally closer to individuals at any layer. Journal of Individual Differences, ((in press)), 2011. [ bib ] |
[16] | Robin I. M. Dunbar. Constraints on the evolution of social institutions and their implications for information flow. Journal of Institutional Economics, (in press), 2011. [ bib ] |
[17] | O. Curry and Robin I. M. Dunbar. Altruism in social networks: evidence for a "kin premium". British Journal of Psychology, ((revised and resubmitted)), 2011. [ bib ] |
[18] | O. Curry and Robin I. M. Dunbar. Why birds of a feather flock together? the effects of similarity on altruism. Social Networks, (submitted), 2011. [ bib ] |
[19] | O. Curry and Robin I. M. Dunbar. Altruism in networks: the effect of connections. Biology Letters, ((in press)), 2011. [ bib ] |
[20] | Pan Hui, Jon Crowcroft, and Eiko Yoneki. Bubble rap: Social-based forwarding in delay tolerant networks. IEEE Transactions on Mobile Computing, ((to appear)), 2011. [ bib ] |
[21] | M. Ostilli, A. L. Ferreira, and J. F. F. Mendes. Critical behavior and correlations on scale-free small-world networks. application to network design. Phys. Rev. E, ((to appear)), 2011. [ bib ] |
[22] | R. A. da Costa, S. N. Dorogovtsev, A. V. Goltsev, and J. F. F. Mendes. "Explosive Percolation" Transition is Actually Continuous. Physical Review Letters, 105(25), December 2010. [ bib | http ] |
[23] | G. J. Baxter, S. N. Dorogovtsev, A. V. Goltsev, and J. F. F. Mendes. Heterogeneous-k-core versus Bootstrap Percolation on Complex Networks. (submitted), December 2010. [ bib | http ] |
[24] | Sam G. B. Roberts and Robin I. M. Dunbar. The costs of family and friends: an 18-month longitudinal study of relationship maintenance and decay. Evolution and Human Behavior, December 2010. [ bib | http ] |
[25] | M. Ostilli and J. F. F. Mendes. Critical phenomena on heterogeneous small-world networks. Europhysics Letters, 92:40013, November 2010. [ bib ] |
[26] | Leucio Antonio Cutillo, Mark Manulis, and Thorsten Strufe. Security and privacy in online social networks. In Handbook of Social Network, Technologies and Applications. Springer, October 2010. [ bib ] |
[27] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Modelling social-aware forwarding in opportunistic networks. In IFIP Performance Evaluation of Computer and Communication Systems (PERFORM 2010), Vienna, Austria, October 2010. [ bib ] |
[28] | S.M. Allen, M.J. Chorley, G.B. Colombo, and R.M. Whitaker. Self adaptation of cooperation in multi-agent content sharing systems. 2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pages 104-113, 27 September - 01 October 2010. [ bib ] |
[29] | C. Boldrini, M. Conti, F. Delmastro, and A. Passarella. Context- and social-aware middleware for opportunistic networks. J. Netw. Comput. Appl., 33:525-541, September 2010. [ bib | http ] |
[30] | Leucio Antonio Cutillo, Refik Molva, and Thorsten Strufe. On the Security and Feasibility of Safebook : a Distributed Privacy-Preserving Online Social Network. In PrimeLife/IFIP Summer School 2010, 6th International Summer School, IFIP AICT 320, Privacy and Identity Management for Life, Helsingborg, Sweden, August 2-6 2010. [ bib ] |
[31] | Mervyn P. Freeman, Nicholas W. Watkins, Eiko Yoneki, and Jon Crowcroft. Rhythm and randomness in human contact. In International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Odense, Denmark, August 2010. [ bib ] |
[32] | Derek G. Murray, Eiko Yoneki, Jon Crowcroft, and Steven Hand. The case for crowd computing. In Proceedings of the second ACM SIGCOMM workshop on Networking, systems, and applications on mobile handhelds, MobiHeld '10, pages 39-44, New Delhi, India, August 2010. ACM. [ bib | http ] |
[33] | Alessandro Sorniotti and Refik Molva. A provably secure secret handshake with dynamic controlled matching. Computers and Security, 29 (5), July 2010. [ bib ] |
[34] | A. L. Ferreira, J. F. F. Mendes, and M. Ostilli. First- and second-order phase transitions in Ising models on small world networks, simulations and comparison with an effective field theory. Physical review. E, Statistical, nonlinear, and soft matter physics, 82(1)(1), July 2010. [ bib | www: ] |
[35] | Carla Balocco and Pietro Liò. Modelling infection spreading control in a hospital isolation room. Journal of Biomedical Science and Engineering, 3(7), July 2010. [ bib | http | .pdf ] |
[36] | Konstantinos Oikonomou, Dimitrios Kogias, and Ioannis Stavrakakis. Probabilistic flooding for efficient information dissemination in random graph topologies. Computer Networks, 54(10):1615-1629, July 2010. [ bib | http ] |
[37] | M. J. Williams, R. M. Whitaker, and S. M. Allen. Decentralised detection of periodic encounter communities in opportunistic networks. Ad Hoc Networks, ((submitted)), June 30 2010. [ bib ] |
[38] | A. V. Goltsev, F. V. de Abreu, S. N. Dorogovtsev, and J. F. F. Mendes. Stochastic cellular automata model of neural networks. Phys. Rev. E, 81(6):061921, June 2010. [ bib ] |
[39] | E. Jaho, M. Karaliopoulos, and I. Stavrakakis. Social similarity as a driver for selfish, cooperative and altruistic behavior. In 4th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC'10), Montreal, Canada, June 2010. [ bib | .pdf ] |
[40] | Chiara Boldrini and Andrea Passarella. HCMM: Modelling spatial and temporal properties of human mobility driven by users' social relationships. Computer Communications, 33(9):1056-1074, June 2010. [ bib | http ] |
[41] | Andrea Guazzini, Pietro Liò, Franco Bagnoli, Andrea Passarella, and Marco Conti. Cognitive network dynamics in chatlines. Procedia Computer Science, 1(issue 1):2355-2362, May 2010. [ bib ] |
[42] | G. J. Baxter, S. N. Dorogovtsev, A. V. Goltsev, and J. F. F. Mendes. Bootstrap Percolation on Complex Networks. Physical review. E, Statistical, nonlinear, and soft matter physics, 82 (1)(1), May 2010. [ bib | http ] |
[43] | Massimo Ostilli, Eiko Yoneki, Ian X.Y. Leung, Jose F.F. Mendes, Pietro Lió, and Jon Crowcroft. Statistical mechanics of rumour spreading in network communities. Procedia Computer Science, Vol. 1(Issue 1):2325 - 2333, May 2010. ICCS 2010. [ bib | http | .pdf ] |
[44] | Michal Kryczka, Ruben Cuevas, Carmen Guerrero, Eiko Yoneki, and Arturo Azcorra. A first step towards user assisted online social networks. In Proceedings of the 3rd Workshop on Social Network Systems, SNS '10, pages 6:1-6:6, Paris, France, April 2010. ACM. [ bib | http ] |
[45] | Alessandro Sorniotti and Refik Molva. Secret interest groups (SIGs) in social networks with an implementation on Facebook. In SAC 2010, 25th ACM Symposium On Applied Computing, pages 621-628, Sierre, Switzerland, March 22-26 2010. [ bib | http ] |
[46] | Abdullatif Shikfa, Melek Onen, and Refik Molva. Bootstrapping security associations in opportunistic networks. In 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pages 147-152. IEEE, March 2010. [ bib | http ] |
[47] | S. N. Dorogovtsev, A. L. Ferreira, A. V. Goltsev, and J. F. F. Mendes. Zero pearson coefficient for strongly correlated growing trees. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 81(3), March 2010. [ bib | www: ] |
[48] | Stuart M. Allen, Gualtiero Colombo, and Roger M. Whitaker. Cooperation through self-similar social networks. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 5(1):4:1-4:29, February 2010. [ bib | http ] |
[49] | P. Pantazopoulos, I. Stavrakakis, A. Passarella, and M. Conti. Efficient social-aware content placement for opportunistic networks. In Seventh International Conference on Wireless On-demand Network Systems and Services, IFIP/IEEE WONS, Kranjska Gora, Slovenia, February, 3-5 2010. [ bib | .pdf ] |
[50] | Andrea Passarella and Marco Conti. Characterising aggregate inter-contact times in heterogeneous opportunistic networks. In IFIP Networking 2011, Valencia, Spain, 9-13 May 2010. [ bib ] |
[51] | E. Jaho, M. Karaliopoulos, and I. Stavrakakis. Analysis of content placement strategies based on social similarity. IEEE Transactions on Parallel and Distributed Systems, ((submitted)), 2010. [ bib ] |
[52] | S. M. Allen, M. J. Chorley, G. B. Colombo, and R. M. Whitaker. Incentivising cooperation between agents for content sharing. In Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, volume 2 of WI-IAT '10, pages 79-84. IEEE Computer Society, 2010. [ bib | http ] |
[53] | Chiara Boldrini. Design and analysis of context-aware forwarding protocols for opportunistic networks. In Proceedings of the Second International Workshop on Mobile Opportunistic Networking, MobiOpp '10, pages 201-202, New York, NY, USA, 2010. ACM. [ bib | http ] |
[54] | Sergey Dorogovtsev. Lectures on Complex Networks. Oxford University Press, Inc., New York, NY, USA, 2010. [ bib ] |
[55] | Abdullatif Shikfa, Melek Önen, and Refik Molva. Privacy and confidentiality in context-based and epidemic forwarding. Computer Communications, 33(13):1493 - 1504, 2010. [ bib | http ] |
[56] | G. Smaragdakis, N. Laoutaris, K. Oikonomou, I.Stavrakakis, and A. Bestavros. Distributed server migration for scalable internet service deployment (to appear). IEEE/ACM Transactions on Networking, 2010. [ bib ] |
[57] | Konstantinos Oikonomou and Ioannis Stavrakakis. Scalable service migration in autonomic network environments. IEEE Journal on Selected Areas in Communications (JSAC), Special Issue on Recent Advances in Autonomic Communications, 28(1):84-94, January 2010. [ bib | www: ] |
[58] | Marco Conti and Mohan Kumar. Opportunities in opportunistic computing. Computer, 43(1):42-50, January 2010. [ bib | http ] |
[59] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Design and performance evaluation of contentplace, a social-aware data dissemination system for opportunistic networks. Comput. Netw., 54(4):589-604, 2010. [ bib ] |
[60] | Konstantinos Oikonomou, Dimitrios Kogias, and Ioannis Stavrakakis. A study of information dissemination under multiple random walkers and replication mechanisms. In MobiOpp '10: Proceedings of the Second International Workshop on Mobile Opportunistic Networking, pages 118-125, New York, NY, USA, 2010. ACM. [ bib ] |
[61] | Stuart M. Allen, Gualtiero Colombo, and Roger M. Whitaker. Uttering: social micro-blogging without the internet. In MobiOpp '10: Proceedings of the Second International Workshop on Mobile Opportunistic Networking, pages 58-64, New York, NY, USA, 2010. ACM. [ bib ] |
[62] | Leucio Antonio Cutillo, Refik Molva, and Thorsten Strufe. Safebook: a privacy preserving online social network leveraging on real-life trust. To appear in "IEEE Communications Magazine", Consumer Communications and Networking Series, December 2009. [ bib ] |
[63] | Eiko Yoneki and Fehmi Ben Abdesslem. Finding a data blackhole in bluetooth scanning. ExtremeCom, August 2009. [ bib | .pdf ] |
[64] | Eiko Yoneki. The importance of data collection for modelling contact networks. In IEEE Workshop on Social Computing with Mobile Phones and Sensors: Modeling, Sensing and Sharing at SocialCom, August 2009. [ bib | .pdf ] |
[65] | Eiko Yoneki, Ioannis Baltopoulos, and Jon Crowcroft. D3N: programming distributed computation in pocket switched networks. In MobiHeld '09: Proceedings of the 1st ACM workshop on Networking, systems, and applications for mobile handhelds, pages 43-48, New York, NY, USA, August 2009. ACM. [ bib | http | .pdf ] |
[66] | Narseo Vallina-Rodriguez, Pan Hui, and Jon Crowcroft. Has anyone seen my Goose? - social network services in developing regions (Invited Paper). In IEEE Workshop on Social Mobile Web (SMW'09), in conjunction with the 2009 IEEE International Conference on Social Computing, August 2009. [ bib | .pdf ] |
[67] | Eiko Yoneki, D Greenfield, and Jon Crowcroft. Dynamics of inter-meeting time in human contact networks. International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Athens, Greece, July 2009. [ bib | .pdf ] |
[68] | Pan Hui and Sonja Buchegger. Groupthink and peer pressure: Social influence in online social network groups. In Proceeding of International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Athens, Greece, July 2009. [ bib | .pdf ] |
[69] | Leucio Antonio Cutillo, Refik Molva, and Thorsten Strufe. Safebook: feasibility of transitive cooperation for privacy on a decentralized social network. The Third IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications, Kos, Greece, June 15 2009. [ bib | http ] |
[70] | Marco Conti, Franca Delmastro, and Andrea Passarella. Social-aware content sharing in opportunistic networks. In 2009 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops, pages 1-3. IEEE, June 2009. [ bib | http ] |
[71] | Abdullatif Shikfa, Melek Önen, and Refik Molva. Privacy in context-based and epidemic forwarding. In AOC 2009. 3rd IEEE International WoWMoM Workshop on Autonomic and Opportunistic Communications, June 15, 2009, Kos, Greece, June 2009. [ bib | .pdf ] |
[72] | Kuang Xu, Pan Hui, Victor O. K. Li, Jon Crowcroft, Vito Latora, and Pietro Liò. Impact of altruism on opportunistic communications. In Proceeding of First IEEE International Conference on Ubiquitous and Future Networks(ICUFN09), Hong Kong China, June 2009. [ bib | .pdf ] |
[73] | Alessandro Sorniotti and Refik Molva. A provably secure secret handshake with dynamic controlled matching. In IFIP SEC 2009, 24th International Information Security Conference, May 18-20, 2009, Pafos, Cyprus, May 2009. [ bib | http | .pdf ] |
[74] | Pan Hui, Kuang Xu, Victor O. K. Li, Jon Crowcroft, Vito Latora, and Pietro Liò. Selfishness, altruism and message spreading in mobile social networks. In Proceeding of First IEEE International Workshop on Network Science For Communication Networks (NetSciCom09), Rio de Janeiro, Brazil, April 24 2009. [ bib | .pdf ] |
[75] | Leucio Antonio Cutillo, Refik Molva, and Thorsten Strufe. Leveraging social links for trust and privacy in networks. In INetSec 2009. Open Research Problems in Network Security. April 23-24, 2009. Zurich, Switzerland, April 23-24, 2009. [ bib | http ] |
[76] | A Peddemors and Eiko Yoneki. Decentralized probabilistic world modeling with cooperative sensing. KiVS, March 2009. [ bib | .pdf ] |
[77] | Nishanth Sastry, Eiko Yoneki, and Jon Crowcroft. Buzztraq: predicting geographical access patterns of social cascades using social networks. In EuroSys workshop on Social Network Systems, March 2009. [ bib | .pdf ] |
[78] | E. Jaho and I. Stavrakakis. Joint interest- and locality-aware content dissemination in social networks. In Sixth Annual Conference on Wireless On demand Network Systems and Services, IFIP/IEEE WONS 2009, Snowbird, Utah, USA, February 2-4 2009. [ bib | .pdf ] |
[79] | Sam G. Roberts, Robin I. Dunbar, Thomas V. Pollet, and Toon Kuppens. Exploring variation in active network size: Constraints and ego characteristics. Social Networks, February 2009. [ bib | http ] |
[80] | M. Conti, F. Delmastro, and A. Passarella. Context-aware p2p over opportunistic networks. Mobile Peer-to-Peer Computing for Next Generation Distributed Environments: Advancing Conceptual and Algorithmic Applications, pages 460-480, 2009. [ bib | http ] |
[81] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Social-based autonomic routing in opportunistic networks. Autonomic Communication, pages 31-67, 2009. [ bib | http ] |
[82] | Chiara Boldrini, Marco Conti, and Andrea Passarella. The sociable traveller: human travelling patterns in social-based mobility. In MobiWAC '09: Proceedings of the 7th ACM international symposium on Mobility management and wireless access, pages 34-41, New York, NY, USA, 2009. ACM. [ bib ] |
[83] | Yu-En Lu, Sam Roberts, Pietro Lio, Robin Dunbar, and Jon Crowcroft. On optimising personal network size to manage information flow. In CIKM '09: Proceedings of the 18th ACM International Conference on Informatio n and Knowledge Management, Complex Network Information and Knowledge Management Workshop, Hong Kong, China, 2009. [ bib | .pdf ] |
[84] | Yu-En Lu, Sam Roberts, Pietro Lio, Robin Dunbar, and Jon Crowcroft. Size matters: variation in personal network size, personality and effect on information transmission. In Proceedings of the IEEE International Conference on Social Computing (Social COM), Vancouver, Canada, 2009. [ bib | .pdf ] |
[85] | Shu Yan Chan, Ian X. Y. Leung, and Pietro Lio. Fast centrality approximation in modular networks. In Proceedings of the 1st ACM International Workshop on Complex Networks in Information and Knowledge Management (CNIKM), pages 31-38, Hong Kong, China, 2009. ACM. [ bib | .pdf ] |
[86] | Ian X. Y. Leung, Pan Hui, Pietro Liò, and Jon Crowcroft. Towards real-time community detection in large networks. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 79(6:066107), 2009. [ bib | http | .pdf ] |
[87] | Leyla Bilge, Thorsten Strufe, Davide Balzarotti, and Engin Kirda. All your contacts are belong to us : Automated identity theft attacks on social networks. In WWW 2009, Madrid, Spain, 2009. [ bib | http ] |
[88] | Leucio Antonio Cutillo, Refik Molva, and Thorsten Strufe. Privacy preserving social networking through decentralization. In WONS 2009, 6th International Conference on Wireless On-demand Network Systems and Services, February 2-4, 2009, Snowbird, Utah, USA, 2009. [ bib | http | http ] |
[89] | S. M. Allen, G. Colombo, and R. M. Whitaker. Forming social networks of trust to incentivize cooperation. In HICSS 2009, 2009. [ bib | http ] |
[90] | Massimo Ostilli and J F F Mendes. Small-world of communities: communication and correlation of the meta-network. Journal of Statistical Mechanics: Theory and Experiment, 2009(08):L08004 (12pp), 2009. [ bib | http ] |
[91] | M. Ostilli and J. F. F. Mendes. Communication and correlation among communities. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 80(1):011142, 2009. [ bib | http ] |
[92] | Stuart M. Allen, Marco Conti, Jon Crowcroft, Robin Dunbar, Pietro Liò, Jose F. Mendes, Refik Molva, Andrea Passarella, Ioannis Stavrakakis, and Roger M. Whitaker. Social networking for pervasive adaptation. In 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW, volume 0, pages 49-54, Los Alamitos, CA, USA, October 2008. IEEE. [ bib | http ] |
[93] | Pan Hui, Jon Crowcroft, and Eiko Yoneki. Bubble rap: social-based forwarding in delay tolerant networks. In MobiHoc '08: Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing, pages 241-250, New York, NY, USA, 2008. ACM. [ bib ] |
[94] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Context and resource awareness in opportunistic network data dissemination. In WOWMOM '08: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks, pages 1-6, Washington, DC, USA, 2008. IEEE Computer Society. [ bib | http ] |
[95] | A. Panagakis, A. Vaios, and I. Stavrakakis. On the performance of two-hop message spreading in DTNs. Ad-Hoc Networks, 2008. [ bib | http ] |
[96] | S. N. Dorogovtsev, J. F. F. Mendes, A. N. Samukhin, and A. Y. Zyuzin. Organization of modular networks. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 78(5):056106, 2008. [ bib | http ] |
[97] | A. V. Goltsev, S. N. Dorogovtsev, and J. F. F. Mendes. Percolation on correlated networks. Physical Review E, 78:051105, 2008. [ bib | http ] |
[98] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Modelling data dissemination in opportunistic networks. In CHANTS '08: Proceedings of the third ACM workshop on Challenged networks, pages 89-96, 2008. [ bib | .pdf ] |
[99] | Chiara Boldrini, Marco Conti, and Andrea Passarella. ContentPlace: social-aware data dissemination in opportunistic networks. In MSWiM '08: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems, pages 203-210, 2008. [ bib | .pdf ] |
[100] | R. Cuevas, E. Jaho, C. Guerrero, and I. Stavrakakis. OnMove: A protocol for content distribution in wireless delay tolerant networks based on social information. In ACM CoNEXT 2008 Student Workshop, 2008. [ bib | .pdf ] |
[101] | S. N. Dorogovtsev, J. F. F. Mendes, A. N. Samukhin, and A. Y. Zyuzin. Organization of modular networks. In Netsci 2008, 2008. [ bib | http | .pdf ] |
[102] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Autonomic behaviour of opportunistic network routing. Int. J. Auton. Adapt. Commun. Syst., 1(1):122-147, 2008. [ bib ] |
[103] | Chiara Boldrini, Marco Conti, and Andrea Passarella. Exploiting users' social relations to forward data in opportunistic networks: The HiBOp solution. Pervasive and Mobile Computing, 4(5):633-657, 2008. [ bib | http ] |
Gualtiero Colombo, Roger M. Whitaker, and Stuart M. Allen. Cooperation in social networks of trust. 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) Workshops, pages 78-83, 2008. [ bib ]
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