An Efficient Data Aggregation Algorithm for Cluster-based Sensor Network

Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energy-efficiency of sensor nodes. One node, called the cluster leader, collects data from surrounding nodes and then sends the summarized information to upstream nodes. In this paper, we propose an algorithm to select a cluster leader that will perform data aggregation in a partially connected sensor network. The algorithm reduces the traffic flow inside the network by adaptively selecting the shortest route for packet routing to the cluster leader. We also describe a simulation framework for functional analysis of WSN applications taking our proposed algorithm as an exampl

Bullying in a networked era: a literature review

This research update presents an aggregation and summary of recent academic literature on youth bullying. The purpose of this document is to “translate” scholarly research for a concerned public audience, which may include but is not limited to parents, caregivers, educators, and practitioners. This translation highlights recent findings and developments in the literature and makes them accessible to the informed but non-expert reader. The document’s two guiding questions are “What is bullying?” (Section I) and “What can be done about bullying?” (Section II). Section I begins with a brief overview of key definitions and related research conversations and then addresses bullying’s prevalence, the types of individuals involved in bullying, the characteristics of individuals involved and the consequences of their involvement, and community-level dynamics related to bullying. Section II covers four areas where action has been taken to address problems associated with bullying – school policy, curricula, school climate, and parents – and ends on a note about approaches that mix or cut across these areas. The purpose is to render lessons learned from research and assessment accessible to those interested in deepening or expanding their knowledge of bullying-related issues

Concepts and evolution of research in the field of wireless sensor networks

The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest and a continuous evolution in the scientific and industrial community. The use of this particular type of ad hoc network is becoming increasingly important in many contexts, regardless of geographical position and so, according to a set of possible application. WSNs offer interesting low cost and easily deployable solutions to perform a remote real time monitoring, target tracking and recognition of physical phenomenon. The uses of these sensors organized into a network continue to reveal a set of research questions according to particularities target applications. Despite difficulties introduced by sensor resources constraints, research contributions in this field are growing day by day. In this paper, we present a comprehensive review of most recent literature of WSNs and outline open research issues in this field

Gossip mechanisms for distributed database systems.

Yam, Shing Chung Jonathan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.Includes bibliographical references (leaves 75-79).Abstracts in English and Chinese.AbstractAcknowledgementContentsList of FiguresList of TablesChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.2Chapter 1.2 --- Thesis Organization --- p.5Chapter 2 --- Literature Review --- p.7Chapter 2.1 --- Data Sharing and Dissemination --- p.7Chapter 2.2 --- Data Aggregation --- p.12Chapter 2.3 --- Sensor Network Database Systems --- p.13Chapter 2.4 --- Data Routing and Networking --- p.23Chapter 2.5 --- Other Applications --- p.24Chapter 3 --- Preliminaries --- p.25Chapter 3.1 --- Probability Distribution and Gossipee-selection Schemes --- p.25Chapter 3.2 --- The Network Models --- p.28Chapter 3.3 --- Objective and Problem Statement --- p.30Chapter 3.4 --- Two-tier Gossip Mechanism --- p.31Chapter 3.5 --- Semantic-dependent Gossip Mechanism --- p.32Chapter 4 --- Results for Two-tier Gossip Mechanisms --- p.34Chapter 4.1 --- Background --- p.34Chapter 4.2 --- A Time Bound for Solving the Clustered Destination Problem with T-Theorem 1 --- p.39Chapter 4.3 --- Further Results´ؤTheorem 2 --- p.49Chapter 4.4 --- Experimental Results for Two-tier and N-tier Gossip Mechanisms --- p.51Chapter 4.4.1 --- Performance Evaluation of Two-tier Gossip Mechanisms --- p.52Chapter 4.4.2 --- Performance Evaluation of N-tier Gossip Mechanisms --- p.56Chapter 4.5 --- Discussion --- p.60Chapter 5 --- Results for Semantic-dependent Gossip Mechanisms --- p.62Chapter 5.1 --- Background --- p.62Chapter 5.2 --- Theory --- p.65Chapter 5.3 --- "Detection of Single Moving Heat Source with S max(2c1l,c1h ))" --- p.66Chapter 5.4 --- Detection of Multiple Static Heat Sources with Two-tier Gossip mechanism --- p.69Chapter 5.5 --- Discussion --- p.72Chapter 6 --- Conclusion --- p.73Chapter 7 --- References --- p.75Appendix Prove of Result 4.3 --- p.8

A Little Bird Told Me So...:the Emotional, Attributional, Relational And Team-Level Outcomes Of Engaging In Gossip

In this paper, I examine the consequences, both positive and negative, of initiating and participating in gossip in work-related contexts. While a commonly held perspective is that gossip is harmful in that it hurts relational interactions by encouraging coalition-building and engendering divisiveness, an alternative hypothesis is that gossip\u27s emotional attributes, can also help to foster stronger relationships and help individuals navigate complex environments. Specifically, I explore the influence of gossip at multiple levels of analysis: individual, dyadic and group. In Study 1, a laboratory experiment that looks at the short-term benefits of engaging in gossip (versus two control conditions, self-disclosure and task discussion), I find that individuals who engage in gossip experience higher positive emotions, energy and motivation but lower levels of state self-esteem. These gossiping dyads also experience dyadic benefits of relationship closeness and cooperation. Study 2 explored both the reputational and team-level outcomes of gossip. This study showed that team members who engaged in gossip were seen as being less trustworthy. Furthermore, gossip centrality had an inverted U-shaped curvilinear relationship with perceptions of competence. Study 2 showed that gossip about team members negatively influenced team outcomes such as psychological safety, cooperation and viability and increased team-level perceptions of politics while gossip about individuals outside the team has a positive effect on these outcomes, enhancing levels of team cooperation and decreasing perceptions of politics at the team-level. More detailed mediation analyses showed that team process variables, psychological safety and perceptions of politics measured halfway through the course of the team, mediated the negative relationship between intra-team gossip density and team cooperation and team viability measured at the end of the team\u27s lifecycle. In terms of the relationship between extra-team gossip density and team cooperation, it was mediated by decreased team perceptions of politics. This research contributes to the emerging field of inquiry on gossip by providing a comprehensive model of the consequences of gossip at three different levels of analysis as well as a strong empirical test of the effect of gossip on organizationally-relevant outcomes

Risk Assessment and Collaborative Information Awareness for Plan Execution

Joint organizational planning and plan execution in risk-prone environment, has seen renewed research interest given its potential for agility and cost reduction. The participants are often asked to quickly plan and execute tasks in partially known or hostile environments. This requires advanced decision support systems for situational response whereby state-of-the-art technologies can be used to handle issues such as plan risk assessment, appropriate information exchange, asset localization and adaptive planning with risk mitigation. Toward this end, this thesis contributes innovative approaches to address these issues, focusing on logistic support over risk-prone transport network as many organizational plans have key logistic components. Plan risk assessment involves property evaluation for vehicle risk exposure, cost bounds and contingency options assessment. Appropriate information exchange involves participant specific shared information awareness under unreliable communication. Asset localization mandates efficient sensor network management. Adaptive planning with risk mitigation entails limited risk exposure replanning, factoring potential vehicle and cargo loss. In this pursuit, this thesis first investigates risk assessment for asset movement and contingency valuation using probabilistic model-checking and decision trees, followed by elaborating a gossip based protocol for hierarchy-aware shared information awareness, also assessed via probabilistic model-checking. Then, the thesis proposes an evolutionary learning heuristic for efficiently managing sensor networks constrained in terms of sensor range, capacity and energy use. Finally, the thesis presents a learning based heuristic for cost effective adaptive logistic planning with risk mitigation. Instructive case studies are also provided for each contribution along with benchmark results evaluating the performance of the proposed heuristic techniques

REPUTATION MANAGEMENT ALGORITHMS IN DISTRIBUTED APPLICATIONS

Nowadays, several distributed systems and applications rely on interactions between unknown agents that cooperate in order to exchange resources and services. The distributed nature of these systems, and the consequent lack of a single centralized point of control, let agents to adopt selfish and malicious behaviors in order to maximize their own utility. To address such issue, many applications rely on Reputation Management Systems (RMSs) to estimate the future behavior of unknown agents before establishing actual interactions. The relevance of these systems is even greater if the malicious or selfish behavior exhibited by a few agents may reduce the utility perceived by cooperative agents, leading to a damage to the whole community. RMSs allow to estimate the expected outcome of a given interaction, thus providing relevant information that can be exploited to take decisions about the convenience of interacting with a certain agent. Agents and their behavior are constantly evolving and becoming even more complex, so it is increasingly difficult to successfully develop the RMS, able to resist the threats presented. A possible solution to this problem is the use of agent-based simulation software designed to support researchers in evaluating distributed reputation management systems since the design phase. This dissertation presents the design and the development of a distributed simulation platform based on HPC technologies called DRESS. This solution allows researchers to assess the performance of a generic reputation management system and provides a comprehensive assessment of its ability to withstand security attacks. In the scientific literature, a tool that allows the comparison of distinct RMS and different design choices through a set of defined metrics, also supporting large-scale simulations, is still missing. The effectiveness of the proposed approach is demonstrated by the application scenario of user energy sharing systems within smart-grids and by considering user preferences differently from other work. The platform has proved to be useful for the development of an energy sharing system among users, which with the aim of maximizing the amount of energy transferred has exploited the reputation of users once learned their preferences