Middleware for social computing: a roadmap
01 May 2012-Journal of Internet Services and Applications (Springer London)-Vol. 3, Iss: 1, pp 117-125
TL;DR: This work identifies three societal grand challenges that are likely to drive future research in social computing and elaborate on how the middleware community can help address them.
Abstract: Social computing broadly refers to supporting social behaviours using computational systems. In the last decade, the advent of Web 2.0 and its social networking services, wikis, blogs, and social bookmarking has revolutionised social computing, creating new online contexts within which people interact socially (social networking). With the pervasiveness of mobile devices and embedded sensors, we stand at the brink of another major revolution, where the boundary between online and offline social behaviours blurs, providing opportunities for (re)defining social conventions and contexts once again. But opportunities come with challenges: can middleware foster the engineering of social software? We identify three societal grand challenges that are likely to drive future research in social computing and elaborate on how the middleware community can help address them.
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TL;DR: This paper presents a novel architecture geared for privacy-sensitive applications where personal information is shared among users and decisions are made based on given optimization criteria, and proposes efficient yet provably-private solutions.
Abstract: The scope of mobile phones has skyrocketed in recent years to such an extent that smartphone sales are expected to surpass those of PCs by the end of 2011. Equipped with relatively powerful processors and fairly large memory and storage capabilities, smartphones can accommodate increasingly complex interactive applications. As a result, the growing amount of sensitive information shared by smartphone users raises serious privacy concerns and motivates the need for appropriate privacy-preserving mechanisms. In this paper, we present a novel architecture geared for privacy-sensitive applications where personal information is shared among users and decisions are made based on given optimization criteria. Specifically, we focus on two application scenarios: (i) privacy-preserving interest sharing, i.e., discovering shared interests without leaking users' private information, and (ii) private scheduling, i.e., determining common availabilities and location preferences that minimize associate costs, without exposing any sensitive information. We propose efficient yet provably-private solutions, and conduct an extensive experimental analysis that attests to the practicality of the attained privacy features.
5 citations
01 Jan 2012
TL;DR: This thesis takes the Robot Operating System, a middleware from the robotics community, and introduces concepts to make the middleware more suitable for Intelligent Environments, including the adoption of the new IPv6 Internet Protocol, concepts to secure the privacy of its users and providing a scalable base to interconnect even the smallest devices from wireless sensor networks with powerful computers like service robots.
Abstract: Recent advancements in the computing power, energy consumption and cost of small electronic computing devices make it possible to create powerful and long lasting (wireless) sensor and actuator systems. In the future, these systems will become part of our daily lives as electric light has become part of our live at the beginning of the 20th century. These networks consisting of sensors and actuators can be used to form Intelligent Environments, which will process data gathered by sensors to enhance our lives with services provided by an intelligent environment, surrounding us. To support this development, new ways have to be found to integrate huge numbers of devices with our current and future networks. The Internet is a success story of open standards and modularity, these concepts can also be applied to this emerging Internet of Things. The Internet is currently performing a transition to a new Internet Protocol, to support even the largest networks. This technology makes it possible to bridge the huge number of future nodes in Wireless Sensor Networks, the Internet of Things, smartphones and service robotics together. To support the development of applications for such a massive amount of nodes and data, abstractions have to be made. By providing a middleware between the applications and the devices, development can be sped up and mechanisms put in place, to preserve the privacy of people living with ever more devices gathering data about their lives. This thesis takes the Robot Operating System, a middleware from the robotics community, and introduces concepts to make the middleware more suitable for Intelligent Environments. This includes the adoption of the new IPv6 Internet Protocol, concepts to secure the privacy of its users and providing a scalable base to interconnect even the smallest devices from wireless sensor networks with powerful computers like service robots.
5 citations
TL;DR: Radiator, a middleware to assist application programmers implementing efficient context propagation mechanisms within their applications makes an efficient use of network bandwidth, arguably the biggest bottleneck in the deployment of large-scale context propagation systems.
Abstract: Applications such as Facebook, Twitter and Foursquare have brought the mass adoption of personal short messages, distributed in (soft) real-time on the Internet to a large number of users. These messages are complemented with rich contextual information such as the identity, time and location of the person sending the message (e.g., Foursquare has millions of users sharing their location on a regular basis, with almost 1 million updates per day). Such contextual messages raise serious concerns in terms of scalability and delivery delay; this results not only from their huge number but also because the set of user recipients changes for each message (as their interests continuously change), preventing the use of well-known solutions such as pub-sub and multicast trees. This leads to the use of non-scalable broadcast based solutions or point-to-point messaging. We propose Radiator, a middleware to assist application programmers implementing efficient context propagation mechanisms within their applications. Based on each user’s current context, Radiator continuously adapts each message propagation path and delivery delay, making an efficient use of network bandwidth, arguably the biggest bottleneck in the deployment of large-scale context propagation systems. Our experimental results demonstrate a 20x reduction on consumed bandwidth without affecting the real-time usefulness of the propagated messages.
5 citations
07 Oct 2013
TL;DR: The AmpliFIRE Support Action as discussed by the authors supports the FIRE Community to prepare FIRE for 2020, by strengthening the exploitation and impact creation capacities of future Internet Research and Experimentation (FIRE) facilities.
Abstract: The over-all mission of the AmpliFIRE Support Action is to support the FIRE Community to prepare FIRE for 2020, by strengthening the exploitation and impact creation capacities of Future Internet Research and Experimentation (FIRE) facilities. AmpliFIRE vision for year 2020, setting out a transition path from the current situation towards a “FIRE Ecosystem” for 2020
3 citations
Dissertation•
19 Mar 2013
TL;DR: It is time to start thinking about the future, not just the present but also the past, in terms of how the authors think about the present.
Abstract: ........................................................................................................................................12 1 Εισαγωγή ........................................................................................................................ 15 2 Ορισμοί και Βασικές Έννοιες ......................................................................................... 20 2.1 Context – Context Awareness ................................................................................ 21 2.2 Context Aware Προγραμματισμός ......................................................................... 26 2.3 Διαχείριση Context ................................................................................................. 29 2.3.1 Συλλογή Context .............................................................................................. 30 2.3.2 Context Συλλογισμός ....................................................................................... 34 2.3.3 Context διαχείριση .......................................................................................... 36 2.4 Λογισμικό πλαίσιο – Πλατφόρμα λογισμικού ........................................................ 40 2.4.1 Πλαίσιο ............................................................................................................ 40 2.4.2 Πλατφόρμα ...................................................................................................... 41 2.5 Ενδιάμεσο Λογισμικό ............................................................................................. 42 2.5.1 Context Aware Ενδιάμεσο Λογισμικό ............................................................. 47 3 Ανασκόπηση Βιβλιογραφίας (State of the Art) ............................................................. 52 4 Webinos ......................................................................................................................... 61 4.1 Όραμα Χαρακτηριστικά webinos ......................................................................... 62 4.2 Λειτουργίες Καινοτομίες webinos ........................................................................ 63 4.3 Τα APIs του webinos ............................................................................................... 67 5 Webinos Context ............................................................................................................ 78 5.1 Διαχειριστής Context webinos ............................................................................... 78 5.1.1 Εισαγωγή ......................................................................................................... 78 5.1.2 Context Λειτουργικότητα ................................................................................ 81 5.1.3 Επισκόπηση Ροής Δεδομένων Διαχειριστή Context ....................................... 84 5.1.4 Context Λεξικό ................................................................................................. 86 5.1.5 Διάγραμμα Ανάπτυξης .................................................................................... 86 5.1.6 Υποκλοπή Μηνύματος και Αποθήκευση ........................................................ 88 5.1.7 Context Querying ............................................................................................ 89 5.1.8 Κανόνες Context .............................................................................................. 90 5.1.9 Προγραμματισμένες Κλήσεις ΑΡΙ .................................................................... 91 5.2 Context Σενάρια & Περιπτώσεις Χρήσης ............................................................... 92 5.2.1 Εντοπισμός χαμένης συσκευής ....................................................................... 92 5.2.2 Τοποθεσία απομακρυσμένης συσκευής ......................................................... 93 5.2.3 Συσκευές Πολλαπλών Χρηστών ...................................................................... 94 5.2.4 Συλλογή και αναπαράσταση Context Δεδομένων .......................................... 95 5.2.5 Συνδυασμός και context λογισμός.................................................................. 96 5.2.6 Φιλτράρισμα για αποφυγή διπλοεγγραφών .................................................. 97 6 References ...................................................................................................................... 99
Additional excerpts
...Σε αυτές τις τεχνολογίες το ενδιάμεσο λογισμικό κτίζονταν σαν ένα ξεχωριστό σύστημα που έπαιρνε είσοδο από την εφαρμογή και παρείχε διαφάνεια στους χρήστες και τους σχεδιαστές των εφαρμογών [8]....
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References
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TL;DR: The amount of data in the authors' world has been exploding, and analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey.
Abstract: The amount of data in our world has been exploding, and analyzing large data sets—so-called big data— will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.
4,700 citations
"Middleware for social computing: a ..." refers background in this paper
...It is estimated that an average of 30 billion pieces of content are shared on Facebook every month, with a 40% projected growth in data per year [25]....
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..., it is estimated that big data has a potential annual value to the US health care system alone of $300 billion [25])....
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01 Jan 2011
TL;DR: The strong version of Richard Wilkinson and Kate Pickett's argument in The Spirit Level implies that President Obama's fight to reform health care was pointless as discussed by the authors, and that extending the availability of health insurance cannot substantially improve Americans’ health.
Abstract: The strong version of Richard Wilkinson and Kate Pickett’s argument in The Spirit Level implies that President Obama’s fight to reform health care was pointless. Extending the availability of health insurance cannot substantially improve Americans’ health. Instead, the president would make us all happier, healthier, and longer-lived, their logic suggests, if he could get the richest, say, 5 percent of Americans to leave the country.
1,339 citations
"Middleware for social computing: a ..." refers background in this paper
...That is because being forcibly told how to use a service is perceived as a sign of disrespect by users, and disrespect has often caused violence in physical societies [50] and, for now, only public outcries in digital systems....
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01 May 1999
TL;DR: This work introduces the concept of context widgets that mediate betweent the environment and the application in the same way graphicalwidgets mediate between the user and the applications.
Abstract: Context-enabled applications are just emerging and promise richer interaction by taking environmental context into account. However, they are difficult to build due to their distributed nature and the use of unconventional sensors. The concepts of toolkits and widget libraries in graphical user interfaces has been tremendously successtil, allowing programmers to leverage off existing building blocks to build interactive systems more easily. We introduce the concept of context widgets that mediate between the environment and the application in the same way graphical widgets mediate between the user and the application. We illustrate the concept of context widgets with the beginnings of a widget library we have developed for sensing presence, identity and activity of people and things. We assess the success of our approach with two example context-enabled applications we have built and an existing application to which we have added context-sensing capabilities.
1,337 citations
"Middleware for social computing: a ..." refers background in this paper
...from [42], where ‘context widgets’ where first introduced to...
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05 Nov 2008
TL;DR: The CenceMe application is presented, which represents the first system that combines the inference of the presence of individuals using off-the-shelf, sensor-enabled mobile phones with sharing of this information through social networking applications such as Facebook and MySpace.
Abstract: We present the design, implementation, evaluation, and user ex periences of theCenceMe application, which represents the first system that combines the inference of the presence of individuals using off-the-shelf, sensor-enabled mobile phones with sharing of this information through social networking applications such as Facebook and MySpace. We discuss the system challenges for the development of software on the Nokia N95 mobile phone. We present the design and tradeoffs of split-level classification, whereby personal sensing presence (e.g., walking, in conversation, at the gym) is derived from classifiers which execute in part on the phones and in part on the backend servers to achieve scalable inference. We report performance measurements that characterize the computational requirements of the software and the energy consumption of the CenceMe phone client. We validate the system through a user study where twenty two people, including undergraduates, graduates and faculty, used CenceMe continuously over a three week period in a campus town. From this user study we learn how the system performs in a production environment and what uses people find for a personal sensing system.
1,184 citations
"Middleware for social computing: a ..." refers background in this paper
...book and MySpace), has been presented [29], with the spe-...
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15 Jun 2010
TL;DR: A comprehensive study of smartphone use finds that qualitative similarities exist among users that facilitate the task of learning user behavior and demonstrates the value of adapting to user behavior in the context of a mechanism to predict future energy drain.
Abstract: Using detailed traces from 255 users, we conduct a comprehensive study of smartphone use. We characterize intentional user activities -- interactions with the device and the applications used -- and the impact of those activities on network and energy usage. We find immense diversity among users. Along all aspects that we study, users differ by one or more orders of magnitude. For instance, the average number of interactions per day varies from 10 to 200, and the average amount of data received per day varies from 1 to 1000 MB. This level of diversity suggests that mechanisms to improve user experience or energy consumption will be more effective if they learn and adapt to user behavior. We find that qualitative similarities exist among users that facilitate the task of learning user behavior. For instance, the relative application popularity for can be modeled using an exponential distribution, with different distribution parameters for different users. We demonstrate the value of adapting to user behavior in the context of a mechanism to predict future energy drain. The 90th percentile error with adaptation is less than half compared to predictions based on average behavior across users.
901 citations
"Middleware for social computing: a ..." refers background in this paper
...If online (web-based) social computing was centred around social networking services (e.g., Facebook, Last.fm, Twitter, MySpace) and the sharing of usergenerated content within users’ individual networks, ubiquitous social computing is going to enable societal services, where people’ actions and dealings will be looked at, in relation to their impact on common welfare....
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...Early work that combines physical data (gathered from sensor-enabled mobile phones) and social data (collected from social networking applications such as Facebook and MySpace), has been presented [29], with the specific goal to sense a user’s activity (e.g., being in the gym, in a conversation)....
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...10http://buddypress.org/. hibit rather different behaviours, as already witnessed on social networking websites like Facebook [14] (e.g., amount of shared content and content quality are not equally distributed across users); different behaviours will result, for example, in different amounts of data being gathered and processed, with direct consequences on QoS parameters, such as network latency and battery consumption....
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...hibit rather different behaviours, as already witnessed on social networking websites like Facebook [14] (e....
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...It is estimated that an average of 30 billion pieces of content are shared on Facebook every month, with a 40% projected growth in data per year [25]....
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