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Wireless Networks. 01/2010; 16:1601-1620.
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ABSTRACT: In this paper we present a MANET proactive routing enhancement scheme by comprehensive evaluation of multiple dynamic routing metrics, including delay, energy cost, and link stability. We developed efficient routing metric prediction methods: predicting delay and energy using double exponential smoothing, and predicting link stability using a heuristic based on the normal-like distributions of the link lifetimes in typical MANET mobility scenarios. The routing metrics predictions are incorporated with regular routing information exchanges. On each node, routing table is constructed by a modified version of Dijkstra's algorithm, which evaluates the predicted metrics values compositively. We integrated such a multi-metric prediction/evaluation mechanism into OLSR and name it OLSR_MC. We show by simulation that OLSR_MC is more adaptive to the network dynamics and therefore is able to improve performance significantly on multiple routing objectives, including higher packet delivery ratio, shorter average end-to-end delay, and prolonged network energy lifetime.
Local Computer Networks, 2007. LCN 2007. 32nd IEEE Conference on; 11/2007
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ABSTRACT: Energy-aware routing in mobile wireless ad hoc networks has been investigated extensively in the framework of reactive routing. In this paper we present an energy preserving mechanism suitable to be integrated with a proactive MANET routing scheme. We use a compositive energy cost, which considers both transmission power consumption and residual energy of the nodes, as the routing metric. Our energy cost calculation is based on prediction of node energy consumption using ARIMA model. The formulation of our energy cost is tailored to heterogeneous MANET in terms of power consumptions. We extended OLSR with our energy preserving mechanism. Our power-aware version of OLSR is proven by simulation to be able to prolong network lifetime significantly in both homogeneous and heterogeneous scenarios in terms of power consumptions.
Wireless Algorithms, Systems and Applications, 2007. WASA 2007. International Conference on; 09/2007
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ABSTRACT: Networks often require a copy of a message to be delivered to every network node. The network-layer can provide this service, referred to as network-wide broadcast routing, or simply "broadcasting". Broadcasting has many applications, including its role as a building block in many routing protocols. In a MANET, simplistic broadcast schemes (such as flooding) inundate the network with redundancy, contention, collision, and energy-inefficiency. This can prevent broadcasts from achieving the objectives of optimal delivery ratio, energy balancing, and latency. As a solution, we propose multiple-criteria broadcasting (MCB). In MCB, the source of each broadcast specifies the importance assigned to broadcast objectives. Network nodes use this policy, along with local and neighbor knowledge, to broadcast in accordance with the objective priorities attributed to the message. Using ns2, the performance of MCB is evaluated and compared to other broadcast protocols. To present knowledge, MCB constitutes the first reconfigurable, multi-objective approach to broadcasting
Local Computer Networks, Proceedings 2006 31st IEEE Conference on; 12/2006
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LCN 2006, The 31st Annual IEEE Conference on Local Computer Networks, Tampa, Florida, USA, 14-16 November 2006; 01/2006
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ABSTRACT: In this paper, we propose an adaptability enhancement mechanism to be integrated with OLSR, and potentially any Mobile Ad Hoc Network (MANET) proactive routing protocol. The key of this mechanism is prediction and evaluation of the mean queuing delay as a routing metric. Neural network methods are used to predict delays. We investigated the pros and cons of using two types of neural networks, namely Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF), in predicting nonstationary time series (e.g., mean queuing delay time series). We present TierUp -- our novel node-state routing table calculation algorithm, which is developed for the integration of delay prediction and OLSR. We name the extended version of OLSR as OLSR_NN. We show through ns2 simulation that compared to OLSR, OLSR_NN is able to increase data packet delivery ratio and reduce average end-to-end delay in scenarios with complex traffic patterns and various node mobility. Our simulation also shows the advantage of using neural network for delay prediction compared to moving average and exponential smoothing. The enhanced adaptability of OLSR_NN is further verified by the more balanced traffic observed in our simulation.
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ABSTRACT: Research on wireless routing protocols have been striving to achieve two important but contradicting goals: adaptability to the dynamic network conditions and efficient routing information diffusion. A possible approach to solve this issue is through intelligent use of the nodes' past experiences of the network traffic conditions, and making predictions on the future network traffic conditions based on the experiences. Delay is a typical routing metric. In this paper, we present a scheme for predicting mean per-packet one-hop delays using neural network approaches. The predicted one-hop delays are then used by the nodes to participate in routing information diffusion. By experiments, we prove the feasibility of predicting mean delays as a time series using either tapped-delay-line multi-layer perceptron (MLP) network or tapped-delay-line radial basis function (RBF) network. Two types of inputs for prediction are used: a) the mean delay time series itself only, b) the mean delay time series together with the corresponding traffic loads. The advantages and limitations of these neural network approaches are discussed
Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on;
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ABSTRACT: Many network emulators have been developed for performance evaluation of network protocols and distributed applications. While most of them specialize on some features targeted for certain applications, few of them address the overall accuracy and efficiency of a general-purpose network emulator. In this paper, we present the key elements of constructing an accurate and efficient general-purpose network emulator. We focus on the architecture of an emulator and the packet capture methods. We analyze the typical approaches a network emulator takes with emphasis on two outstanding distributed network emulators: NETShaper and EMPOWER. We present the functions we have added to NETShaper, namely zero bandwidth emulation and bit error rate emulation. Application of distributed network emulation to protocol design for inter-planetary networks is also discussed
Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on;
