Ashutosh Deepak Gore

Link Scheduling Algorithms for Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have the potential of being a cost effective solution to provide connectivity and coverage in both urban and rural areas. Typically, a WMN is a backbone network that carries high data rate traffic and employs Time Division Multiple Access (TDMA) like access mechanisms. For a WMN to provide high throughput, the design of an efficient link scheduling algorithm is of paramount importance. Towards this end, we provide an overview of link scheduling algorithms in Spatial TDMA wireless mesh networks. These algorithms can be classified into three categories: those based only on a communication graph model of the network, those based on a communication graph model and Signal to Interference and Noise Ratio (SINR) threshold conditions at receivers and those based on an SINR graph model of the network. We first outline a framework for modeling STDMA networks. We review representative research works and provide the description of an algorithm from each of these classes. We describe the relative merits and demerits of each class of algorithms and compare their performance via simulations. We conclude with a discussion on practical implementation of these algorithms and open research problems.

On High Spatial Reuse Link Scheduling in STDMA Wireless Ad Hoc Networks

We consider the point-to-point link scheduling problem in Spatial Time Division Multiple Access (STDMA) wireless ad hoc networks, motivate the use of spatial reuse as performance metric and provide an explicit characterization of spatial reuse. We assume uniform transmission power at all nodes and propose an algorithm based on a graph model of the network as well as Signal to Interference and Noise Ratio (SINR) computations. Our algorithm achieves higher spatial reuse than existing algorithms, without compromising on computational complexity.

Comments on "On the connectivity in finite ad hoc networks"

The probability of connectivity of a one-dimensional finite ad hoc network formed by n nodes uniformly distributed in [0, z] was derived by Desai and Manjunath (2002). In this letter, we provide two interpretations of their analysis, thus correcting and complementing their results

Power-Controlled FCFS Splitting Algorithm for Wireless Networks

We consider random access in wireless networks under a physical interference model, wherein a receiver is capable of power-based capture, i.e., a packet can be correctly decoded in the presence of multiple transmissions if the received signal-to-interference-plus-noise ratio (SINR) exceeds a threshold. We propose a splitting algorithm that varies the transmission power of users on the basis of quaternary channel feedback (idle, success, capture, and collision). We show that our algorithm achieves a maximum stable throughput of 0.5518. Simulation results demonstrate that our algorithm achieves higher throughput and lower delay than those of first-come-first-serve and residual-energy-based splitting algorithms with uniform transmission power.

Correction to "Comments on 'On the connectivity in finite ad hoc networks'"

The probability of connectivity of a one-dimensional finite ad hoc network was derived by Desai and Manjunath, and further analyzed by Gore. In this letter, we point out a discrepancy, thus corroborating the original result. However, it provides the exact interpretation of the recursion and derives the probability of connectivity of a one-dimensional finite sensor network.

Power Controlled FCFS Splitting Algorithm for Wireless Networks

We consider random access in wireless networks under the physical interference model, wherein the receiver is capable of power-based capture, i.e., a packet can be decoded correctly in the presence of multiple transmissions if the received Signal to Interference and Noise Ratio exceeds a threshold. We propose a splitting algorithm that varies the transmission powers of users on the basis of quaternary channel feedback (idle, success, capture, collision). We show that our algorithm achieves a maximum stable throughput of 0.5518. Simulation results demonstrate that our algorithm achieves higher throughput and lower delay than the First Come First Serve splitting algorithm with uniform transmission power.