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Abstract-Code updates, such as those for debugging purposes, are frequent and expensive in the early development stages of wireless sensor network applications. We propose AdapCode, a reliable data dissemination protocol that uses adaptive network coding to reduce broadcast traffic in the process of code updates. Packets on every node are coded by linear combination and decoded by Gaussian elimination. The core idea in AdapCode is to adaptively change the coding scheme according to the link quality. Our evaluation shows that AdapCode uses up to 40% less packets than Deluge in large networks. In addition, AdapCode performs much better in terms of load balancing, which prolongs the system lifetime, and has a slightly shorter propagation delay. Finally, we show that network coding is doable on sensor networks in that (i) it imposes only a 3 byte header overhead, (ii) it is easy to find linearly independent packets, and (3) Gaussian elimination needs only 1KB of memory.

Providing differentiated Quality of Service (QoS) over unreliable wireless channels is an important challenge for supporting several future applications. We analyze a model that has been proposed to describe the QoS requirements by four criteria: traffic pattern, channel reliability, delay bound, and throughput bound. We study this mathematical model and extend it to handle variable bit rate applications. We then obtain a sharp characterization of schedulability vis-a-vis latencies and timely throughput. Our results extend the results so that they are general enough to be applied on a wide range of wireless applications, including MPEG Variable-BitRate (VBR) video streaming, VoIP with differentiated quality, and wireless sensor networks (WSN).Two major issues concerning QoS over wireless are admission control and scheduling. Based on the model incorporating the QoS criteria, we analytically derive a necessary and sufficient condition for a set of variable bit-rate clients to be feasible. Admission control is reduced to evaluating the necessary and sufficient condition. We further analyze two scheduling policies that have been proposed, and show that they are both optimal in the sense that they can fulfill every set of clients that is feasible by some scheduling algorithms. The policies are easily implemented on the IEEE 802.11 standard. Simulation results under various settings support the theoretical study.

We develop a general approach for designing scheduling policies for real-time traffic over wireless channels. We extend prior work, which characterizes a real-time flow by its traffic pattern, delay bound, timely-throughput requirement, and channel reliability, to allow time-varying channels, allow clients to have different deadlines, and allow for the optional employment of rate adaptation. Thus, our model allow the treatment of more realistic fading channels as well as scenarios with mobile nodes, and the usage of more general transmission strategies.We derive a sufficient condition for a scheduling policy to be feasibility optimal, and thereby establish a class of feasibility optimal policies. We demonstrate the utility of the identified class by deriving a feasibility optimal policy for the scenario with rate adaptation, time-varying channels, and heterogeneous delay bounds. When rate adaptation is not available, we also derive a feasibility optimal policy for timevarying channels. For the scenario where rate adaptation is not available but clients have different delay bounds, we describe a heuristic. Simulation results are also presented which indicate the usefulness of the scheduling policies for more realistic and complex scenarios.978-1-4244-5837-0/10/$26.00

We develop a general approach for designing scheduling policies for real-time traffic over wireless channels. We extend prior work, which characterizes a real-time flow by its traffic pattern, delay bound, timely-throughput requirement, and channel reliability, to allow time-varying channels, allow clients to have different deadlines, and allow for the optional employment of rate adaptation. Thus, our model allow the treatment of more realistic fading channels as well as scenarios with mobile nodes, and the usage of more general transmission strategies.We derive a sufficient condition for a scheduling policy to be feasibility optimal, and thereby establish a class of feasibility optimal policies. We demonstrate the utility of the identified class by deriving a feasibility optimal policy for the scenario with rate adaptation, time-varying channels, and heterogeneous delay bounds. When rate adaptation is not available, we also derive a feasibility optimal policy for timevarying channels. For the scenario where rate adaptation is not available but clients have different delay bounds, we describe a heuristic. Simulation results are also presented which indicate the usefulness of the scheduling policies for more realistic and complex scenarios.