OpenBU

Forewarding in Mobile Opportunistic Networks

OpenBU

Show simple item record

dc.contributor.author Erramilli, Vijay en_US
dc.date.accessioned 2011-10-20T04:51:49Z
dc.date.available 2011-10-20T04:51:49Z
dc.date.issued 2009 en_US
dc.identifier.uri http://hdl.handle.net/2144/1722
dc.description.abstract Recent advances in processor speeds, mobile communications and battery life have enabled computers to evolve from completely wired to completely mobile. In the most extreme case, all nodes are mobile and communication takes place at available opportunities – using both traditional communication infrastructure as well as the mobility of intermediate nodes. These are mobile opportunistic networks. Data communication in such networks is a difficult problem, because of the dynamic underlying topology, the scarcity of network resources and the lack of global information. Establishing end-to-end routes in such networks is usually not feasible. Instead a store-and-carry forwarding paradigm is better suited for such networks. This dissertation describes and analyzes algorithms for forwarding of messages in such networks. In order to design effective forwarding algorithms for mobile opportunistic networks, we start by first building an understanding of the set of all paths between nodes, which represent the available opportunities for any forwarding algorithm. Relying on real measurements, we enumerate paths between nodes and uncover what we refer to as the path explosion effect. The term path explosion refers to the fact that the number of paths between a randomly selected pair of nodes increases exponentially with time. We draw from the theory of epidemics to model and explain the path explosion effect. This is the first contribution of the thesis, and is a key observation that underlies subsequent results. Our second contribution is the study of forwarding algorithms. For this, we rely on trace driven simulations of different algorithms that span a range of design dimensions. We compare the performance (success rate and average delay) of these algorithms. We make the surprising observation that most algorithms we consider have roughly similar performance. We explain this result in light of the path explosion phenomenon. While the performance of most algorithms we studied was roughly the same, these algorithms differed in terms of cost. This prompted us to focus on designing algorithms with the explicit intent of reducing costs. For this, we cast the problem of forwarding as an optimal stopping problem. Our third main contribution is the design of strategies based on optimal stopping principles which we refer to as Delegation schemes. Our analysis shows that using a delegation scheme reduces cost over naive forwarding by a factor of O(√N), where N is the number of nodes in the network. We further validate this result on real traces, where the cost reduction observed is even greater. Our results so far include a key assumption, which is unbounded buffers on nodes. Next, we relax this assumption, so that the problem shifts to one of prioritization of messages for transmission and dropping. Our fourth contribution is the study of message prioritization schemes, combined with forwarding. Our main result is that one achieves higher performance by assigning higher priorities to young messages in the network. We again interpret this result in light of the path explosion effect. en_US
dc.description.sponsorship Thomson Research, Paris; National Science Foundation (CCR-0325701, ANI-0322990); HAGGLE FET Project; Erramilli family. en_US
dc.language.iso en_US en_US
dc.publisher Boston University Computer Science Department en_US
dc.relation.ispartofseries BUCS Technical Reports;BUCS-TR-2008-030 en_US
dc.title Forewarding in Mobile Opportunistic Networks en_US
dc.type Technical Report en_US
etd.degree.name Doctor of Philosophy
etd.degree.level doctoral
etd.degree.discipline Computer Science
etd.degree.grantor Boston University


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search OpenBU


Browse

Deposit Materials

Statistics