The Network Simulator-3 (ns-3) is rapidly developing into a flexible and easy-to-use tool suitable for wireless network simulation. Since energy consumption is a key issue for wireless devices, wireless network researchers often need to investigate the energy consumption at a battery powered node or in the overall network, while running network simulations. This requires the underlying simulator to support energy consumption and energy source modeling. Currently however, ns-3 does not provide any support for modeling energy consumption or energy sources. In this paper, we introduce an integrated energy framework for ns-3, with models for energy source as well as energy consumption. We present the design and implementation of the overall framework and the specific models therein. Further, we show how the proposed framework can be used in ns-3 to simulate energy-aware protocols in a wireless network.

Abstract-Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network's ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.

Body Sensor Networks (BSNs) consist of miniature sensors deployed on or implanted into the human body for health monitoring. Conserving the energy of these sensors, while guaranteeing a required level of performance, is a key challenge in BSNs. In terms of communication protocols, this translates to minimizing energy consumption while limiting the latency in data transfer. In this paper, we focus on polling-based communication protocols for BSNs, and address the problem of optimizing the polling schedule to achieve minimal energy consumption and latency. We show that this problem can be posed as a geometric program, which belongs to the class of convex optimization problems, solvable in polynomial time. We also introduce a dynamic priority vector for each sensor, based on the observation that relative priorities of sensors in a BSN change over time. This vector is used to develop a decision-tree based approach for resolving scheduling conflicts among devices. The proposed framework is applicable to a broad class of periodic polling-based communication protocols. We design one such protocol in detail and show that it achieves an improvement of approximately 45% over the widely accepted standard IEEE 802.15.4 MAC protocol.

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