Copyright
IIT Kharagpur
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Abstract
Large size networks e.g. Internet, Peer- to-Peer (P2P) networks, wireless sensor networks (WSN), computing grid etc. are all pervasive and possess some unique features like constrained resource (bandwidth, battery power, node processing capacity, etc.), bursty Internet traffic due to flash crowds and peer churn in P2P networks. These features affect the design of different information management services like search, dissemination, gathering and routing of information. The broad objective of this thesis is to understand how these features affect the performance of the service algorithms and from the understanding design scalable and robust algorithms to enhance the performance of the existing ones. Specifically, we address the problem of coverage, routing and search.
Large networks are inherently decentralized and unstructured where all information management services, in general are required to maximize network coverage. Our first objective is to design an optimal coverage algorithm under bandwidth and latency constraints. To fulfill the above objective, we define the following fundamental and novel problem: Starting from a single node and without memory of visited nodes, maximize node coverage in a given time T under bandwidth constraint B. We designed an optimal coverage algorithm based on random walk proliferation for infinite d-dimensional Euclidean lattice (with d > 2) that achieve Cmax (coverage achieved by 1-RW) in O(B(d- 2)/d ) times faster than a single random walker, implying significant that speed-up is achievable even without sacrificing efficiency. Further, for any real-world service requiring a higher speed-up than O(B(d-2)/d ), we extend the optimal algorithm to a generalized class of proliferation algorithms, which can be used to efficiently cover the entire (B , T ) spectrum. Our results are applicable for designing services in networks with homogeneous node degrees like WSNs and implementing service differentiation.
Inspired by the fact that Internet traffic contains sudden bursts due to frequent occurrence of ‘flash crowds’, our second objective is to design a set of dynamic routing algorithms for handling bursty traffic. We design dynamic routing algorithms which can effectively detect the sudden occurrence of traffic bursts using only local I formation (neighbor
Copyright
IIT Kharagpur
- 2 -
degree and buffer occupancy) and adapt suitably to tackle it. The efficacy of our algorithms have been demonstrated through extensive simulation under varying burst traffic rates, considering both constant and degree dependent node capacities. The results show that in terms of mean packet delivery time and throughput, the proposed algorithms outperform the existing routing algorithms which were tested either under uniform Poisson-like traffic distributions or under periodic fluctuating traffic. Our results give an indication that dynamic routing may be used as an easy to deploy and cost effective alternative option to combat flash crowds in the Internet.
Measurements on popular file-sharing P2P networks reveal good correlation between content stored and content searched by an user. Noting the above fact, our third objective is to design a light-weight, self-adjusting, robust (churn-resistant) search algorithm which can simultaneously form interest-based loosely-structured P2P overlays and perform efficient search on it. Contrary to flooding, the algorithm relies on forwarding of query packets. Performance comparison with existing flood-based algorithms both in absence and presence of churn on power-law network topology as well as real Gnutella trace, show that (a) proliferation-based query forwarding is a better alternative to query flooding, in terms of search efficiency, within communities and (b) query success probability remains unchanged even under 50% churn. Our study substantiated the claim that formation of loose-structured communities can be an elegant method to design scalable P2P search algorithms, even under high churn rate.
In a nutshell, we observed that in addition to the large size, the challenge of designing scalable service algorithms also arises due to the inherent resource constraint and dynamics which must be taken into account in their design and performance comparisons.
Keywords: Unstructured search, Coverage, Routing, Euclidean lattice, Power law, Traffic burst, Congestion, Self-organized search, Peer-to-peer, Content-based communities.
