1,289 research outputs found
Maximizing Routing Throughput with Applications to Delay Tolerant Networks
abstract: Many applications require efficient data routing and dissemination in Delay Tolerant Networks (DTNs) in order to maximize the throughput of data in the network, such as providing healthcare to remote communities, and spreading related information in Mobile Social Networks (MSNs). In this thesis, the feasibility of using boats in the Amazon Delta Riverine region as data mule nodes is investigated and a robust data routing algorithm based on a fountain code approach is designed to ensure fast and timely data delivery considering unpredictable boat delays, break-downs, and high transmission failures. Then, the scenario of providing healthcare in Amazon Delta Region is extended to a general All-or-Nothing (Splittable) Multicommodity Flow (ANF) problem and a polynomial time constant approximation algorithm is designed for the maximum throughput routing problem based on a randomized rounding scheme with applications to DTNs. In an MSN, message content is closely related to users’ preferences, and can be used to significantly impact the performance of data dissemination. An interest- and content-based algorithm is developed where the contents of the messages, along with the network structural information are taken into consideration when making message relay decisions in order to maximize data throughput in an MSN. Extensive experiments show the effectiveness of the above proposed data dissemination algorithm by comparing it with state-of-the-art techniques.Dissertation/ThesisDoctoral Dissertation Computer Science 201
Scalable download protocols
Scalable on-demand content delivery systems, designed to effectively handle increasing request rates, typically use service aggregation or content replication techniques. Service aggregation relies on one-to-many communication techniques, such as multicast, to efficiently deliver content from a single sender to multiple receivers. With replication, multiple geographically distributed replicas of the service or content share the load of processing client requests and enable delivery from a nearby server.Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. Analytic lower bounds developed in this thesis show that neither of these protocols consistently yields performance close to optimal. New hybrid protocols are proposed that achieve within 20% of the optimal delay in homogeneous systems, as well as within 25% of the optimal maximum client delay in all heterogeneous scenarios considered.In systems utilizing both service aggregation and replication, well-designed policies determining which replica serves each request must balance the objectives of achieving high locality of service, and high efficiency of service aggregation. By comparing classes of policies, using both analysis and simulations, this thesis shows that there are significant performance advantages in using current system state information (rather than only proximities and average loads) and in deferring selection decisions when possible. Most of these performance gains can be achieved using only “local” (rather than global) request information.Finally, this thesis proposes adaptations of already proposed peer-assisted download techniques to support a streaming (rather than download) service, enabling playback to begin well before the entire media file is received. These protocols split each file into pieces, which can be downloaded from multiple sources, including other clients downloading the same file. Using simulations, a candidate protocol is presented and evaluated. The protocol includes both a piece selection technique that effectively mediates the conflict between achieving high piece diversity and the in-order requirements of media file playback, as well as a simple on-line rule for deciding when playback can safely commence
Energy Efficient and Guaranteed Packet Delivery in Mobile Ad Hoc Networks
For Ad-hoc network routing protocols, high delivery ratio with low energy consumption is one of design challenges. This paper identifies the limitations of ad hoc routing scheme, in terms of guaranteed delivery with low energy consumption. Accordingly, this paper describe a scheme, in which data is forwarded along a pre-established lone path to save energy, and a high delivery ratio is completed by path repair whenever a break is detected. This paper propose a humble, quick, local path repairing method, whereby a malicious node can be tracked by low energy. This paper implement encoding and compression technique scheme and compare its performance with those of pure lone path without repair and multi-path routing schemes
Algorithmic Aspects of Energy-Delay Tradeoff in Multihop Cooperative Wireless Networks
We consider the problem of energy-efficient transmission in delay constrained
cooperative multihop wireless networks. The combinatorial nature of cooperative
multihop schemes makes it difficult to design efficient polynomial-time
algorithms for deciding which nodes should take part in cooperation, and when
and with what power they should transmit. In this work, we tackle this problem
in memoryless networks with or without delay constraints, i.e., quality of
service guarantee. We analyze a wide class of setups, including unicast,
multicast, and broadcast, and two main cooperative approaches, namely: energy
accumulation (EA) and mutual information accumulation (MIA). We provide a
generalized algorithmic formulation of the problem that encompasses all those
cases. We investigate the similarities and differences of EA and MIA in our
generalized formulation. We prove that the broadcast and multicast problems
are, in general, not only NP hard but also o(log(n)) inapproximable. We break
these problems into three parts: ordering, scheduling and power control, and
propose a novel algorithm that, given an ordering, can optimally solve the
joint power allocation and scheduling problems simultaneously in polynomial
time. We further show empirically that this algorithm used in conjunction with
an ordering derived heuristically using the Dijkstra's shortest path algorithm
yields near-optimal performance in typical settings. For the unicast case, we
prove that although the problem remains NP hard with MIA, it can be solved
optimally and in polynomial time when EA is used. We further use our algorithm
to study numerically the trade-off between delay and power-efficiency in
cooperative broadcast and compare the performance of EA vs MIA as well as the
performance of our cooperative algorithm with a smart noncooperative algorithm
in a broadcast setting.Comment: 12 pages, 9 figure
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