Opportunistic linked data querying through approximate membership metadata

Between URI dereferencing and the SPARQL protocol lies a largely unexplored axis of possible interfaces to Linked Data, each with its own combination of trade-offs. One of these interfaces is Triple Pattern Fragments, which allows clients to execute SPARQL queries against low-cost servers, at the cost of higher bandwidth. Increasing a client's efficiency means lowering the number of requests, which can among others be achieved through additional metadata in responses. We noted that typical SPARQL query evaluations against Triple Pattern Fragments require a significant portion of membership subqueries, which check the presence of a specific triple, rather than a variable pattern. This paper studies the impact of providing approximate membership functions, i.e., Bloom filters and Golomb-coded sets, as extra metadata. In addition to reducing HTTP requests, such functions allow to achieve full result recall earlier when temporarily allowing lower precision. Half of the tested queries from a WatDiv benchmark test set could be executed with up to a third fewer HTTP requests with only marginally higher server cost. Query times, however, did not improve, likely due to slower metadata generation and transfer. This indicates that approximate membership functions can partly improve the client-side query process with minimal impact on the server and its interface

Simplifying Wireless Social Caching

Social groups give the opportunity for a new form of caching. In this paper, we investigate how a social group of users can jointly optimize bandwidth usage, by each caching parts of the data demand, and then opportunistically share these parts among themselves upon meeting. We formulate this problem as a Linear Program (LP) with exponential complexity. Based on the optimal solution, we propose a simple heuristic inspired by the bipartite set-cover problem that operates in polynomial time. Furthermore, we prove a worst case gap between the heuristic and the LP solutions. Finally, we assess the performance of our algorithm using real-world mobility traces from the MIT Reality Mining project dataset and two mobility traces that were synthesized using the SWIM model. Our heuristic performs closely to the optimal in most cases, showing a better performance with respect to alternative solutions.Comment: Parts of this work were accepted for publication in ISIT 2016. A complete version is submitted to Transactions on Mobile Computin

Corpus for development of routing algorithms in opportunistic networks

We have designed a collection of scenarios, a corpus, for its use in the study and development of routing algorithms for opportunistic networks. To obtain these scenarios, we have followed a methodology based on characterizing the space and choosing the best exemplary items in such a way that the corpus as a whole was representative of all possible scenarios. Until now, research in this area was using some sets of non-standard network traces that made it difficult to evaluate algorithms and perform fair comparisons between them. These developments were hard to assess in an objective way, and were prone to introduce unintentional biases that directly affected the quality of the research. Our contribution is more than a collection of scenarios; our corpus provides a fine collection of network behaviors that suit the development of routing algorithms, specifically in evaluating and comparing them. If the scientific community embraces this corpus, the community will have a global-agreed methodology where the validity of results would not be limited to specific scenarios or network conditions, thus avoiding self-produced evaluation setups, availability problems and selection bias, and saving time. New research in the area will be able to validate the routing algorithms already published. It will also be possible to identify the scenarios better suit specific purposes, and results will be easily verified. The corpus is available free to download and use

Message forwarding techniques in Bluetooth enabled opportunistic communication environment

These days, most of the mobile phones are smart enough with computer like intelligence and equipped with multiple communication technologies such as Bluetooth, wireless LAN, GPRS and GSM. Different communication medium on single device have unlocked the new horizon of communication means. Modern mobile phones are not only capable of using traditional way of communication via GSM or GPRS; but, also use wireless LANs using access points where available. Among these communication means, Bluetooth technology is very intriguing and unique in nature. Any two devices equipped with Bluetooth technology can communicate directly due to their unique IDs in the world. This is opposite to GSM or Wireless LAN technology; where devices are dependent on infrastructure of service providers and have to pay for their services. Due to continual advancement in the field of mobile technology, mobile ad-hoc network seems to be more realised than ever using Bluetooth. In traditional mobile ad-hoc networks (MANETs), before information sharing, devices have partial or full knowledge of routes to the destinations using ad-hoc routing protocols. This kind of communication can only be realised if nodes follow the certain pattern. However, in reality mobile ad-hoc networks are highly unpredictable, any node can join or leave network at any time, thus making them risky for effective communication. This issue is addressed by introducing new breed of ad-hoc networking, known as opportunistic networks. Opportunistic networking is a concept that is evolved from mobile ad-hoc networking. In opportunistic networks nodes have no prior knowledge of routes to intended destinations. Any node in the network can be used as potential forwarder with the exception of taking information one step closer to intended destination. The forwarding decision is based on the information gathered from the source node or encountering node. The opportunistic forwarding can only be achieved if message forwarding is carried out in store and forward fashion. Although, opportunistic networks are more flexible than traditional MANETs, however, due to little insight of network, it poses distinct challenges such as intermittent connectivity, variable delays, short connection duration and dynamic topology. Addressing these challenges in opportunistic network is the basis for developing new and efficient protocols for information sharing. The aim of this research is to design different routing/forwarding techniques for opportunistic networks to improve the overall message delivery at destinations while keeping the communication cost very low. Some assumptions are considered to improved directivity of message flow towards intended destinations. These assumptions exploit human social relationships analogies, approximate awareness of the location of nodes in the network and use of hybrid communication by combining several routing concept to gain maximum message directivity. Enhancement in message forwarding in opportunistic networks can be achieved by targeting key nodes that show high degree of influence, popularity or knowledge inside the network. Based on this observation, this thesis presents an improved version of Lobby Influence (LI) algorithm called as Enhanced Lobby Influence (ELI). In LI, the forwarding decision is based on two important factors, popularity of node and popularity of node’s neighbour. The forwarding decision of Enhanced Lobby Influence not only depends on the intermediate node selection criteria as defined in Lobby Influence but also based on the knowledge of previously direct message delivery of intended destination. An improvement can be observed if nodes are aware of approximate position of intended destinations by some communication means such as GPS, GSM or WLAN access points. With the knowledge of nodes position in the network, high message directivity can be achieved by using simple concepts of direction vectors. Based on this observation, this research presents another new algorithm named as Location-aware opportunistic content forwarding (LOC). Last but not least, this research presents an orthodox yet unexplored approach for efficient message forwarding in Bluetooth communication environment, named as Hybrid Content Forwarding (HCF). The new approach combines the characteristics of social centrality based forwarding techniques used in opportunistic networks with traditional MANETs protocols used in Bluetooth scatternets. Simulation results show that a significant increase in delivery radio and cost reduction during content forwarding is observed by deploying these proposed algorithms. Also, comparison with existing technique shows the efficiency of using the new schemes

Towards efficacy and efficiency in sparse delay tolerant networks

The ubiquitous adoption of portable smart devices has enabled a new way of communication via Delay Tolerant Networks (DTNs), whereby messages are routed by the personal devices carried by ever-moving people. Although a DTN is a type of Mobile Ad Hoc Network (MANET), traditional MANET solutions are ill-equipped to accommodate message delivery in DTNs due to the dynamic and unpredictable nature of people\u27s movements and their spatio-temporal sparsity. More so, such DTNs are susceptible to catastrophic congestion and are inherently chaotic and arduous. This manuscript proposes approaches to handle message delivery in notably sparse DTNs. First, the ChitChat system [69] employs the social interests of individuals participating in a DTN to accurately model multi-hop relationships and to make opportunistic routing decisions for interest-annotated messages. Second, the ChitChat system is hybridized [70] to consider both social context and geographic information for learning the social semantics of locations so as to identify worthwhile routing opportunities to destinations and areas of interest. Network density analyses of five real-world datasets is conducted to identify sparse datasets on which to conduct simulations, finding that commonly-used datasets in past DTN research are notably dense and well connected, and suggests two rarely used datasets are appropriate for research into sparse DTNs. Finally, the Catora system is proposed to address congestive-driven degradation of service in DTNs by accomplishing two simultaneous tasks: (i) expedite the delivery of higher quality messages by uniquely ordering messages for transfer and delivery, and (ii) avoid congestion through strategic buffer management and message removal. Through dataset-driven simulations, these systems are found to outperform the state-of-the-art, with ChitChat facilitating delivery in sparse DTNs and Catora unencumbered by congestive conditions --Abstract, page iv

Fast community structure local uncovering by independent vertex-centred process

This paper addresses the task of community detection and proposes a local approach based on a distributed list building, where each vertex broadcasts basic information that only depends on its degree and that of its neighbours. A decentralised external process then unveils the community structure. The relevance of the proposed method is experimentally shown on both artificial and real data.Comment: 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug 2015, Paris, France. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Minin