Seva Shneer

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MaxWeight scheduling algorithms provide an effective mechanism for achieving queue stability and guaranteeing maximum throughput in a wide variety of scenarios. The maximum-stability guarantees however rely on the fundamental premise that the system consists of a fixed set of sessions with stationary ergodic traffic processes. In the present paper we(More)
The goal of jointly providing efficiency and fairness in wireless networks can be seen as the problem of maximizing a given utility function. In contrast with wired networks, the capacity of wireless networks is typically time-varying and not known explicitly. Hence, as the capacity region is impossible to know or measure exactly, existing scheduling(More)
Carrier-Sense Multiple-Access (CSMA) protocols form a popular class of random-access schemes for regulating node activity in wireless networks. We compare the continuous and the time-slotted versions of this protocol in the saturated regime, and show that continuous CSMA has higher aggregate throughput than the slotted protocol, but this comes at the cost(More)
The goal of jointly providing fairness and efficiency in wireless networks can be seen as the problem of maximizing a given utility function. The main difficulty when solving this problem is that the capacity region of wireless networks is typically unknown and time-varying, which prevents the usage of traditional optimization tools. As a result, scheduling(More)
CSMA/CA is a popular random-access algorithm for wireless networks, but its stability properties are poorly understood. We consider a linear multi-hop network of three nodes where the neighbouring nodes interfere with each other and medium access is governed by the CSMA/CA algorithm. We assume that the source node is saturated and packets are forwarded(More)
We look at bandwidth-sharing networks where bandwidth allocations are not known to maximize a priori any utility function. Instead, we only require the allocation functions to be 0-homogeneous and concave, which are desirable properties in many situations. We show that a certain gradient condition is necessary and sufficient for such allocations to solve(More)
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