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: The architectural evolution required to ensure that the rollout and deployment of smart city technologies is smooth through acknowledging and integrating the strengths of both the system architectures proposed is discussed.
Abstract: Smart cities have rapidly become a hot topic within technology communities, and promise both improved delivery of services to end users and reduced environmental impact in an era of unprecedented urbanization. Both large hightech companies and grassroots citizen-led initiatives have begun exploring the potential of these technologies. Significant barriers remain to the successful rollout and deployment of business models outlined for smart city applications and services, however. Most of these barriers pertain to an ongoing battle between two main schools of thought for system architecture, ICT and telecommunications, proposed for data management and service creation. Both of these system architectures represent a certain type of value chain and the legacy perspective of the respective players that wish to enter the smart city arena. Smart cities services, however, utilize components of both the ICT industry and mobile telecommunications industries, and do not benefit from the current binary perspective of system architecture. The business models suggested for the development of smart cities require a longterm strategic view of system architecture evolution. This article discusses the architectural evolution required to ensure that the rollout and deployment of smart city technologies is smooth through acknowledging and integrating the strengths of both the system architectures proposed.
178 citations
Cites background from "Middleware for social computing: a ..."
...Much of the proposed analysis of data within a smart city context is useless without the social context [4] of the data, however....
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...…have as their basis " the ability to access much broader and bigger amounts of data, linked to the individuals and the society of which they are the fabric: for example Radio Frequency Identification (RFID) -based smartcards give a fine-grained picture of how public transport is being used " [4]....
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TL;DR: Mayer-Schonberger as discussed by the authors is the director of the Information and Informatics Institute at Princeton University, New Jersey, US$24.95 (hardback), ISBN 978•0•691•13861•9
Abstract: by Viktor Mayer‐Schonberger, Princeton, NJ, Princeton University Press, 2009, 237 pp., US$24.95 (hardback), ISBN 978‐0‐691‐13861‐9 Viktor Mayer‐Schonberger is the director of the Information and In...
138 citations
TL;DR: A practical implementation and experimental evaluations of S-Aframe are presented to demonstrate its reliability and efficiency in terms of computation and communication performance on popular mobile devices and a VSN-based smart ride application is developed to demonstrate the functionality and practical usefulness of the framework.
Abstract: This paper presents S-Aframe, an agent-based multilayer framework with context-aware semantic service (CSS) to support the development and deployment of context-aware applications for vehicular social networks (VSNs) formed by in-vehicle or mobile devices used by drivers, passengers, and pedestrians. The programming model of the framework incorporates features that support collaborations between mobile agents to provide communication services on behalf of owner applications, and service (or resident) agents to provide application services on mobile devices. Using this model, different self-adaptive applications and services for VSNs can be effectively developed and deployed. Built on top of the mobile devices’ operating systems, the framework architecture consists of framework service layer, software agent layer and owner application layer. Integrated with the proposed novel CSS, applications developed on the framework can autonomously and intelligently self-adapt to rapidly changing network connectivity and dynamic contexts of VSN users. A practical implementation and experimental evaluations of S-Aframe are presented to demonstrate its reliability and efficiency in terms of computation and communication performance on popular mobile devices. In addition, a VSN-based smart ride application is developed to demonstrate the functionality and practical usefulness of S-Aframe.
41 citations
Cites methods from "Middleware for social computing: a ..."
...In CSS, we mainly consider three types of semanticbased models for VSN applications developed on S-Aframe: (i) application specific service; (ii) context information; and (iii) user-specified information. a: APPLICATION SPECIFIC SERVICE OF...
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04 May 2015
TL;DR: A novel application-oriented service collaboration (ASCM) model is introduced which can automatically match multiple users with multiple mobile crowd sensing tasks in VSNs in an efficient manner and a context information management model is proposed that aims to enable the mobile community sensing applications to autonomously match appropriate service and information with different users (requesters and participants) in crowdsensing.
Abstract: Driving is an integral part of our everyday lives, and the average driving time of people globally is increasing to 84 minutes everyday, which is a time when people are uniquely vulnerable. A number of research works have identified that mobile crowd sensing in vehicular social networks (VSNs) can be effectively used for many purposes and bring huge economic benefits, e.g., safety improvement and traffic management. This paper presents our effort that toward context-aware mobile crowd sensing in VSNs. First, we introduce a novel application-oriented service collaboration (ASCM) model which can automatically match multiple users with multiple mobile crowd sensing tasks in VSNs in an efficient manner. After that, for users' dynamic contexts of VSNs, we proposes a context information management model, that aims to enable the mobile crowd sensing applications to autonomously match appropriate service and information with different users (requesters and participants) in crowdsensing.
12 citations
Cites background or methods from "Middleware for social computing: a ..."
...…of the service requester (i.e., crowdsensing requester) is compared to that of the service provider (i.e., crowdsensing participant), and their similarity is measured using traditional service matching by simple string or key-word matching, e.g., location based, identities based methods [20]....
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...Compared to other alternative approaches over dynamic networks [20, 22], the proposed CSS has the following advantages....
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07 Apr 2014
TL;DR: It is shown that a city's glocality, measured with social media data, effectively signals the city's economic well-being.
Abstract: Urban resources are allocated according to socio-economic indicators, and rapid urbanization in developing countries calls for updating those indicators in a timely fashion. The prohibitive costs of census data collection make that very difficult. To avoid allocating resources upon outdated indicators, one could partly update or complement them using digital data. It has been shown that it is possible to use social media in developed countries (mainly UK and USA) for such a purpose. Here we show that this is the case for Brazil too. We analyze a random sample of a microblogging service popular in that country and accurately predict the GDPs of 45 Brazilian cities. To make these predictions, we exploit the sociological concept of glocality, which says that economically successful cities tend to be involved in interactions that are both local and global at the same time. We indeed show that a city's glocality, measured with social media data, effectively signals the city's economic well-being.
6 citations
References
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15 Jun 2010
TL;DR: Darwin is the first system that applies distributed machine learning techniques and collaborative inference concepts to mobile phones and it is demonstrated that Darwin improves the reliability and scalability of the proof-of-concept speaker recognition application without additional burden to users.
Abstract: We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on mobile phones. Darwin advances mobile phone sensing through the deployment of efficient but sophisticated machine learning techniques specifically designed to run directly on sensor-enabled mobile phones (i.e., smartphones). Darwin tackles three key sensing and inference challenges that are barriers to mass-scale adoption of mobile phone sensing applications: (i) the human-burden of training classifiers, (ii) the ability to perform reliably in different environments (e.g., indoor, outdoor) and (iii) the ability to scale to a large number of phones without jeopardizing the "phone experience" (e.g., usability and battery lifetime). Darwin is a collaborative reasoning framework built on three concepts: classifier/model evolution, model pooling, and collaborative inference. To the best of our knowledge Darwin is the first system that applies distributed machine learning techniques and collaborative inference concepts to mobile phones. We implement the Darwin system on the Nokia N97 and Apple iPhone. While Darwin represents a general framework applicable to a wide variety of emerging mobile sensing applications, we implement a speaker recognition application and an augmented reality application to evaluate the benefits of Darwin. We show experimental results from eight individuals carrying Nokia N97s and demonstrate that Darwin improves the reliability and scalability of the proof-of-concept speaker recognition application without additional burden to users.
255 citations
10 Apr 2011
TL;DR: This paper presents Quick Community Adaptation (QCA), an adaptive modularity-based method for identifying and tracing community structure of dynamic online social networks and demonstrates the bright applicability of the algorithm via a realistic application on routing strategies in MANETs.
Abstract: Social networks exhibit a very special property: community structure. Understanding the network community structure is of great advantages. It not only provides helpful information in developing more social-aware strategies for social network problems but also promises a wide range of applications enabled by mobile networking, such as routings in Mobile Ad Hoc Networks (MANETs) and worm containments in cellular networks. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social activities and interactions are evolving rapidly. Can we quickly and efficiently identify the network community structure? Can we adaptively update the network structure based on previously known information instead of recomputing from scratch? In this paper, we present Quick Community Adaptation (QCA), an adaptive modularity-based method for identifying and tracing community structure of dynamic online social networks. Our approach has not only the power of quickly and efficiently updating network communities, through a series of changes, by only using the structures identified from previous network snapshots, but also the ability of tracing the evolution of community structure over time. To illustrate the effectiveness of our algorithm, we extensively test QCA on real-world dynamic social networks including ENRON email network, arXiv e-print citation network and Facebook network. Finally, we demonstrate the bright applicability of our algorithm via a realistic application on routing strategies in MANETs. The comparative results reveal that social-aware routing strategies employing QCA as a community detection core outperform current available methods.
226 citations
26 Sep 2010
TL;DR: Locaccino, a mobile location sharing system, was deployed in a four week long field study, where the behavior of study participants who shared their location with their acquaintances was examined, showing that users appear more comfortable sharing their presence at locations visited by a large and diverse set of people.
Abstract: The rapid adoption of location tracking and mobile social networking technologies raises significant privacy challenges. Today our understanding of people's location sharing privacy preferences remains very limited, including how these preferences are impacted by the type of location tracking device or the nature of the locations visited. To address this gap, we deployed Locaccino, a mobile location sharing system, in a four week long field study, where we examined the behavior of study participants (n=28) who shared their location with their acquaintances (n=373.) Our results show that users appear more comfortable sharing their presence at locations visited by a large and diverse set of people. Our study also indicates that people who visit a wider number of places tend to also be the subject of a greater number of requests for their locations. Over time these same people tend to also evolve more sophisticated privacy preferences, reflected by an increase in time- and location-based restrictions. We conclude by discussing the implications our findings.
176 citations
"Middleware for social computing: a ..." refers background in this paper
...scenarios, is that locations are not perceived by users simply as geographic coordinates, but as places within which they conduct social activities [24]; state-of-the-art privacy preserving schemes for location thus cater for different users’ privacy requirements as they vary depending on their sociological interpretation of places [49]....
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26 Sep 2010
TL;DR: Significant differences are found in terms of users' decisions about what location information to share, their privacy concerns, and how privacy-preserving their disclosures were in social-driven location sharing.
Abstract: The popularity of micro-blogging has made general-purpose information sharing a pervasive phenomenon. This trend is now impacting location sharing applications (LSAs) such that users are sharing their location data with a much wider and more diverse audience. In this paper, we describe this as social-driven sharing, distinguishing it from past examples of what we refer to as purpose-driven location sharing. We explore the differences between these two types of sharing by conducting a comparative two-week study with nine participants. We found significant differences in terms of users' decisions about what location information to share, their privacy concerns, and how privacy-preserving their disclosures were. Based on these results, we provide design implications for future LSAs.
174 citations
01 Dec 2004
TL;DR: "MiddleWhere" a distributed middleware infrastructure for location that separates applications from location detection technologies and enables the fusion of different location sensing technologies and facilitates the incorporation of additional location technologies on the fly as they become available is introduced.
Abstract: Location awareness significantly enhances the functionality of ubiquitous computing services and applications, and enriches the way they interact with users and resources in the environment. Many different alternative or complementary location sensing technologies are available. However, these technologies give location information in different formats and with different resolution and confidence. In this paper we introduce "MiddleWhere" a distributed middleware infrastructure for location that separates applications from location detection technologies. MiddleWhere enables the fusion of different location sensing technologies and facilitates the incorporation of additional location technologies on the fly as they become available. MiddleWhere utilizes probabilistic reasoning techniques to resolve conflicts and deduce the location of people given different sensor data. Besides, it allows applications to determine various kinds of spatial relationships between mobile objects and their environment, which is key in enabling a strong coupling between the physical and virtual world, as emphasized by ubiquitous computing. We have integrated MiddleWhere with our ubiquitous computing infrastructure, and have verified its flexibility and usefulness by incorporating various location sensing technologies and building a number of location-sensitive applications on top of it.
164 citations