619 research outputs found

    A one hop overlay system for Mobile Ad Hoc Networks

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    Peer-to-Peer (P2P) overlays were initially proposed for use with wired networks. However, the very rapid proliferation of wireless communication technology has prompted a need for adoption of P2P systems in mobile networks too. There are many common characteristics between P2P overlay networks and Mobile Ad-hoc Networks (MANET). Self-organization, decentralization, a dynamic nature and changing topology are the most commonly shared features. Furthermore, when used together, the two approaches complement each other. P2P overlays provide data storage/retrieval functionality and MANET provides wireless connectivity between clients without depending on any pre-existing infrastructure. P2P overlay networks can be deployed over MANET to address content discovery issues. However, previous research has shown that deploying P2P systems straight over MANET does not exhibit satisfactory performance. Bandwidth limitation, limited resources and node mobility are some of the key constraints. This thesis proposes a novel approach, OneHopOverlay4MANET, to exploit the synergies between MANET and P2P overlays through cross-layering. It combines Distributed Hash Table (DHT) based structured P2P overlays with MANET underlay routing protocols to achieve one logical hop between any pair of overlay nodes. OneHopOverlay4MANET constructs a cross-layer channel to permit direct exchange of routing information between the Application layer, where the overlay operates, and the MANET underlay layer. Consequently, underlay routing information can be shared and used by the overlay. Thus, OneHopOverlay4MANET reduces the typical management traffic when deploying traditional P2P systems over MANET. Moreover, as a result of building one hop overlay, OneHopOverlay4MANET can eliminate the mismatching issue between overlay and underlay and hence resolve key lookups in a short time, enhancing the performance of the overlay. v In this thesis, we present OneHopOverlay4MANET and evaluate its performance when combined with different underlay routing protocols. OneHopOverlay4MANET has been combined with two proactive underlays (OLSR and BATMAN) and with three reactive underlay routing protocols (DSR, AODV and DYMO). In addition, the performance of the proposed system over OLSR has been compared to two recent structured P2P over MANET systems (MA-SP2P and E-SP2P) that adopted OLSR as the routing protocol. The results show that better performance can be achieved using OneHopOverlay4MANET

    Optimal Network Control in Partially-Controllable Networks

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    The effectiveness of many optimal network control algorithms (e.g., BackPressure) relies on the premise that all of the nodes are fully controllable. However, these algorithms may yield poor performance in a partially-controllable network where a subset of nodes are uncontrollable and use some unknown policy. Such a partially-controllable model is of increasing importance in real-world networked systems such as overlay-underlay networks. In this paper, we design optimal network control algorithms that can stabilize a partially-controllable network. We first study the scenario where uncontrollable nodes use a queue-agnostic policy, and propose a low-complexity throughput-optimal algorithm, called Tracking-MaxWeight (TMW), which enhances the original MaxWeight algorithm with an explicit learning of the policy used by uncontrollable nodes. Next, we investigate the scenario where uncontrollable nodes use a queue-dependent policy and the problem is formulated as an MDP with unknown queueing dynamics. We propose a new reinforcement learning algorithm, called Truncated Upper Confidence Reinforcement Learning (TUCRL), and prove that TUCRL achieves tunable three-way tradeoffs between throughput, delay and convergence rate

    Design and evaluation of a peer-to-peer MANET crosslayer approach: OneHopOverlay4MANET

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    Peer-to-Peer overlay networks can be deployed over Mobile Ad hoc Networks (MANET) to address content discovery issues. However, previous research has shown that deploying P2P systems straight over MANET do not exhibit satisfactory performance. Bandwidth limitation, limited resources and node mobility are some of the key constraints. OneHopOverlay4MANET exploits the synergies between MANET and P2P overlays through cross-layering. It combines Distributed Hash Table (DHT) based structured P2P overlays with MANET underlay routing protocols to achieve one logical hop between any pair of overlay nodes. In this paper, we present OneHopOverlay4MANET and evaluate its performance when combined with different underlay routing protocols. We evaluate OneHopOverlay4MANET with two proactive underlay (OLSR and BATMAN) and with three reactive underlay routing protocols (DSR, AODV and DYMO). Through simulation we show that the use of OLSR in OneHopOverlay4MANET yields the best performance. In addition, we compare the performance of the proposed system over OLSR to two recent structured P2P over MANET systems (MA-SP2P and E-SP2P) that adopted OLSR as the routing protocol. As simulation result shows, better performance can be achieved using OneHopOverlay4MANET

    Performance evaluation of OnehopMANET

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    When used together, Peer-to-Peer overlays and MANET complement each other well. While MANET provides wireless connectivity without depending on any pre-existing infrastructure, P2P overlays provide data storage/retrieval functionality. However, both systems face common challenges: maintaining connectivity in dynamic and decentralized networks. In this paper we evaluate the performance of OnehopMANET[1] as a structured P2P over MANET system that uses cross-layering with a proactive underlay. We compare the performance of OnehopMANET with two recent structured P2P over MANET systems (MA-SP2P and E-SP2P) that use the same underlay protocol (OLSR) and that have been shown to outperform other proposals. Through simulation we show that OnehopMANET achieves a better performance in terms of file discovery delay, lookup fail rate and total traffic load for all the simulated scenarios
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