Distributed Algorithms for Scheduling on Line and Tree Networks

We have a set of processors (or agents) and a set of graph networks defined over some vertex set. Each processor can access a subset of the graph networks. Each processor has a demand specified as a pair of vertices $$, along with a profit; the processor wishes to send data between $u$ and $v$. Towards that goal, the processor needs to select a graph network accessible to it and a path connecting $u$ and $v$ within the selected network. The processor requires exclusive access to the chosen path, in order to route the data. Thus, the processors are competing for routes/channels. A feasible solution selects a subset of demands and schedules each selected demand on a graph network accessible to the processor owning the demand; the solution also specifies the paths to use for this purpose. The requirement is that for any two demands scheduled on the same graph network, their chosen paths must be edge disjoint. The goal is to output a solution having the maximum aggregate profit. Prior work has addressed the above problem in a distibuted setting for the special case where all the graph networks are simply paths (i.e, line-networks). Distributed constant factor approximation algorithms are known for this case. The main contributions of this paper are twofold. First we design a distributed constant factor approximation algorithm for the more general case of tree-networks. The core component of our algorithm is a tree-decomposition technique, which may be of independent interest. Secondly, for the case of line-networks, we improve the known approximation guarantees by a factor of 5. Our algorithms can also handle the capacitated scenario, wherein the demands and edges have bandwidth requirements and capacities, respectively.Comment: Accepted to PODC 2012, full versio

Link Expiration Time and Minimum Distance Spanning Trees based Distributed Data Gathering Algorithms for Wireless Mobile Sensor Networks

The high-level contributions of this paper are the design and development of two distributed spanning tree-based data gathering algorithms for wireless mobile sensor networks and their exhaustive simulation study to investigate a complex stability vs. node-network lifetime tradeoff that has been hitherto not explored in the literature. The topology of the mobile sensor networks changes dynamically with time due to random movement of the sensor nodes. Our first data gathering algorithm is stability-oriented and it is based on the idea of finding a maximum spanning tree on a network graph whose edge weights are predicted link expiration times (LET). Referred to as the LET-DG tree, the data gathering tree has been observed to be more stable in the presence of node mobility. However, stability-based data gathering coupled with more leaf nodes has been observed to result in unfair use of certain nodes (the intermediate nodes spend more energy compared to leaf nodes), triggering pre-mature node failures eventually leading to network failure (disconnection of the network of live nodes). As an alternative, we propose an algorithm to determine a minimum-distance spanning tree (MST) based data gathering tree that is more energy-efficient and prolongs the node and network lifetimes, at the cost frequent tree reconfigurations

Analysis of Structured and Un-Structured Network Protocols for Data Aggregation Over Distributed Wireless Sensor Networks

The focus of this thesis is on design and evaluation of one-shot data aggregation protocols for static and mobile wireless sensor networks (WSNs). The goal in one-shot data aggregation is to compute a statistical summary of sensor data such as max, average, sum, count and min, when initiated by a special node such as the base station. WSNs have wide range of applications in both static and mobile/dynamic systems. Static sensor networks are especially useful when monitoring is required in harsh, inaccessible environments and when the region to be monitored is really large. Examples of static sensor network applications include environmental monitoring systems, monitoring of industrial control systems, monitoring of degradation in slagging gasifiers, distributed object detection and tracking. Example of mobile applications include vehicular ad-hoc networks and networks of personal radios used in emergency dispatch and battlefields.;For data aggregation in static networks with stable links, structured approaches such as spanning trees are generally preferred. This is because, once a data aggregation structure has been established, link topologies remain fixed and there is minimal need to actively maintain and change the routing structures. In this thesis, one such tree based data aggregation protocol has been designed and evaluated using simulations in networks ranging from 100-1000 nodes. The protocol has also been implemented at a smaller scale in the context of a smart refractory environment, where slag penetration in gasifiers is remotely monitored using smart bricks that are embedded with sensors. In mobile networks and networks with frequent link changes, topology driven structures are likely to be unstable and to incur a high communication overhead. Therefore, self-repelling random walks have been recently proposed as an attractive alternative for data aggregation in mobile systems. In this thesis, a brief overview of random walk based data aggregation has been presented and systematic evaluation of tree based and random walk based data aggregation protocols in networks ranging from 100-1000 nodes under varying degrees of node mobility has been done. The conditions under which unstructured protocols become more attractive in terms of convergence time and messaging efficiency as compared to tree based structured approaches have been quantified

A new degree six modified chordal ring network topology

The performance of a parallel or distributed network depends on the design of its interconnection topology. One good network interconnection topology that has been the focus of various researchers is the chordal ring. In this paper, a new degree six modified chordal ring is presented, the optimised degree six 3-modified chordal ring (CHR6o3), with the aim of comparing its performance parameters in terms of optimal diameter and optimal average path length to existing degree six chordal rings. Formulae to generate the data for each different chordal ring were derived from its corresponding tree visualisation or used from previous work. Network sizes tested were from 1200 to 12000 nodes. Large networks of CHR6o3 were shown to perform better than those of previous degree six chordal rings. This gives CHR6o3 an added advantage for its implementation in large distributive networks, such as Fibre to the Home (FTTH) networks, since it offers redundancies at higher network layers