Analysis of a Rumor Routing Protocol with Limited Packet Lifetimes

Wireless sensor networks require specialized protocols that conserve power and minimize network traffic. Therefore, it is vitally important to analyze how the parameters of a protocol affect these metrics. In doing so, a more efficient protocol can be developed. This research evaluates how the number of nodes in a network, time between generated agents, lifetime of agents, number of agent transmissions, time between generated queries, lifetime of queries, and node transmission time affect a modified rumor routing protocol for a large-scale, wireless sensor network. Furthermore, it analyzes how the probability distribution of certain protocol parameters affects the network performance. The time between generated queries had the greatest effect upon a network’s energy consumption, accounting for 73.64% of the total variation. An exponential query interarrival distribution with a rate of 0.4 queries/second/node used 25.78% less power than an exponential distribution with a rate of 0.6 queries/second/node. The node transmission time was liable for 73.99% of the total variation in proportion of query failures. Of three distributions, each with a mean of 0.5 seconds, the proportion of query failures using a Rayleigh transmission time distribution was 14.23% less than an exponential distribution and 18.46% less than a uniform distribution. Lastly, 54.85% of the total variation in the mean proportion of time a node is uninformed was a result of the time between generated agents. The mean proportion of time a node is uninformed using an exponential agent interarrival distribution with a rate of 0.005 was 6.59% higher than an exponential distribution with a rate of 0.01

Various demand side management techniques and its role in smart grid–the state of art

The current lifestyle of humanity relies heavily on energy consumption, thus rendering it an inevitable need. An ever-increasing demand for energy has resulted from the increasing population. Most of this demand is met by the traditional sources that continuously deplete and raise significant environmental issues. The existing power structure of developing nations is aging, unstable, and unfeasible, further prolonging the problem. The existing electricity grid is unstable, vulnerable to blackouts and disruption, has high transmission losses, low quality of power, insufficient electricity supply, and discourages distributed energy sources from being incorporated. Mitigating these problems requires a complete redesign of the system of power distribution. The modernization of the electric grid, i.e., the smart grid, is an emerging combination of different technologies designed to bring about the electrical power grid that is changing dramatically. Demand side management (DSM) allow customers to be more involved in contributors to the power systems to achieve system goals by scheduling their shiftable load. Effective DSM systems require the participation of customers in the system that can be done in a fair system. This paper focuses primarily on techniques of DSM and demand responses (DR), including scheduling approaches and strategies for optimal savings

Zonal Energy Management and Optimization System (ZEMOS) for Smart Grid Applications

In the context of implementing the smart grid, electric energy consumption, generation resources, should be managed and optimized in a way that saves energy, improves efficiency, enhances reliability and maintains security while meeting the increasing demand at minimum operating cost. In order to achieve these objectives, there is a need to implement an efficient Zonal Energy Management and Optimization Systems (ZEMOS) that address both existing and future challenges possibly imposed by the use of renewable energy generators that lead to bi-directional power flow instead of unidirectional as in the traditional grids while operate in a coordinated way for the benefit of the whole electric grid. The proposed ZEMOS contains custom defined built-in functions in modular form, which could easily be integrated with other existing energy monitoring systems in the zone of interest (i.e. industrial facility, commercial centers, testing facility, sub-system of the utility service area, educational institutions, power plant, etc.). The proposed ZEMOS provides functions that ensure energy saving, improved reliability, increased efficiency and enhanced utilization of distributed resources: generation energy storage and loads without compromising the tasks carried within that zone. Those module-based systems are characterized by their scalability and flexibility, since more functions can be added down the road as needed. This is necessary in order to accommodate the constant changes imposed by the smart grid and avoid the need to change the whole infrastructure. The proposed ZEMOS performance was investigated for study zones that involve single and multi-objective operations. Besides, study zones with more than single decision makers were also considered in this thesis. Accordingly, the implementation of ZEMOS satisfies the outlined objectives for specific study zone which leads to a reduction in greenhouse gas emission, the improvement of the energy generation portfolio, a reliance on the optimized renewable energy source and a reduction in the energy losses while ensuring high power quality. Furthermore, managing the energy consumption and optimizing the operation of such sizable zones (at Mega Watts scale) ensures significant economic benefits in terms of energy saving, better utilization of available resources, improving the efficiency of energy systems, and exporting novel smart grid technologies, which will lay the foundation to meet future challenges using existing infrastructure

Strategies to Overcome Network Congestion in Infrastructure Systems

Networked Infrastructure systems deliver services and/or products from point to point along the network. They include transportation networks (e.g., rails, highways, airports, sea ports), telecommunication networks (by frequency-bounded airwaves or cables), and utilities (e.g., electric power, water, gas, oil, sewage). Each is a fixed capacity system having marked time-of-day and day-of-week patterns of demand. Usually, the statistics of demand, including hourly patterns (i.e., means and variances) are well known and often correlated with outside factors such as weather (short term) and the general economy (longer term)

A cluster based communication architecture for distributed applications in mobile ad hoc networks

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2006Includes bibliographical references (leaves: 63-69)Text in English; Abstract: Turkish and Englishx, 85 leavesIn this thesis, we aim to design and implement three protocols on a hierarchical architecture to solve the balanced clustering, backbone formation and distributed mutual exclusion problems for mobile ad hoc network(MANET)s. Our ¯rst goal is to cluster the MANET into balanced partitions. Clustering is a widely used approach to ease implemen-tation of various problems such as routing and resource management in MANETs. We propose the Merging Clustering Algorithm(MCA) for clustering in MANETs that merges clusters to form higher level of clusters by increasing their levels. Secondly, we aim to con-struct a directed ring topology across clusterheads which were selected by MCA. Lastly, we implement the distributed mutual exclusion algorithm based on Ricart-Agrawala algo-rithm for MANETs(Mobile RA). Each cluster is represented by a coordinator node on the ring which implements distributed mutual exclusion algorithm on behalf of any member in the cluster it represents. We show the operations of the algorithms, analyze their time and message complexities and provide results in the simulation environment of ns2

Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio