Self-Organizing Social Networks by Preference Similarity and the Networking Capacity of their Users

Consider the decision faced by the user of a social media site of whether or not to accept a friendship request from another user, given the limited amount of information available before deciding. We formalize the problem by defining the expected utility trade-offs derived from the request and simulate the resulting incentives numerically. These incentives provide the basis on which to build social networks determined by the different expectations and preferences of their users. Social networks are generated using a self-organizing map to cluster the decision makers (DMs) by their friendship acceptance behaviour. This behaviour is determined by the distribution of requesters relative to the preferences of the DMs

Social Justice Documentary: Designing for Impact

Explores current methodologies for assessing social issue documentary films by combining strategic design and evaluation of multiplatform outreach and impact, including documentaries' role in network- and field-building. Includes six case studies

Evaluating Mobility Pattern Space Routing for DTNs

Because a delay tolerant network (DTN) can often be partitioned, the problem of routing is very challenging. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high-dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and the large scale evaluation of this routing scheme in the context of ambient networking by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visit of nodes for each possible location. We show that the MobySpace can achieve good performance compared to that of the other algorithms we implemented, especially when we perform routing on the nodes that have a high connection time. We determine that the degree of homogeneity of mobility patterns of nodes has a high impact on routing. And finally, we study the ability of nodes to learn their own mobility patterns.Comment: IEEE INFOCOM 2006 preprin

An Effective Peer to Peer Video Sharing Scheme with Social Reciprocity

Online video sharing and social networking are self-fertilizing speedily in today’s Internet. Online social network users are flooding more video contents among each other. A fascinating development as it is, the operational challenge in previous video streaming systems persists, i.e., the large server load required for topping of the systems. Exploring the unique advantages of a social networking based video streaming system; it advocate utilizing social reciprocities among peers with social relationships for efficient involvement incentivization and development, so as to enable high quality video streaming with low server cost. Then why only video: because more people prefer watching videos. Videos induce people to stay longer on websites. People remember videos. It achievement social reciprocity with two give-and-take ratios at each peer: (1) peer contribution ratio (PCR), which calculates the reciprocity level between a couple of social friends, and (2) system contribution ratio (SCR), which records the give-and-take level of the user to & from the entire system. It expect efficient Peer to Peer mechanisms for video streaming using the two ratios, where each user optimally chooses which other users to seek relay help from and help in relaying video streams, respectively, based on combined evaluations of their social relationship and historical reciprocity levels. This design helps to gain effective incentives for resource contribution, load balancing among relay peers, and efficient social-aware resource scheduling, security to the videos and high prefetching accuracy. DOI: 10.17762/ijritcc2321-8169.15071

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Moderating Effect of Culture on Consumers’ Usage of Social Networks and Its’ Impact on Online Purchase Intentions

This research explored the relationship between Perceived Usefulness and Perceived Ease of the use of Social Network and their impact on Online Purchase Intention moderated by Culture. The data of 384 consumers of online stores belonging to Karachi, Pakistan were taken thorough questionnaire and was analyzed using Structural Equation Modelling to identify the relationship between the said variables and the moderating effect of culture.  The study found positive impact of perceived usefulness and perceived ease of use of social media use for online purchase intention. It also proved the moderating role of culture between use of social media and buying behavior. Thus, culture plays positive effect in influencing buying behavior through perceives usefulness and perceives ease of use. Keywords: Perceived Usefulness, Perceived Ease of Use, Online Purchase Intention, Culture, SEM, Pakistan DOI: 10.7176/JMCR/55-04 Publication date: April 30th 201