Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi Approach

The rapid deployment of wireless sensor network (WSN) poses the challenge of finding optimal locations for the network nodes, especially so in (i) unknown and (ii) obstacle-rich environments. This paper addresses this challenge with BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm. In line with the scenario challenges, BISON nodes are restricted to (i) locally sensed as well as (ii) noisy information on the basis of which they move, avoid obstacles and connect with neighboring nodes. Performance is measured as (i) the percentage of area covered, (ii) the total distance traveled by the nodes, (iii) the cumulative energy consumption and (iv) the uniformity of nodes distribution. Obstacle constellations and noise levels are studied systematically and a collision-free recovery strategy for failing nodes is proposed. Results obtained from extensive simulations show the algorithm outperforming previously reported approaches in both, convergence speed, as well as deployment cost.Comment: 17 pages, 24 figures, 1 tabl

Multi-agent systems and their role in future energy grids

This report documents the program and the outcomes of Dagstuhl Seminar 14181 “Multi-agent systems and their role in future energy grids”. A number of recent events (e. g. Fukushima, Japan, and the largest blackout in history, India) have once again increased global attention on climate change and resource depletion. The evaluation of the feasibility of current approaches for future energy generation, distribution, transportation, and consumption has become an important requirement for most countries. There is a general consensus on the need for a fundamental transformation of future energy grids. The development of an information and communication technology (ICT) support infrastructure was identified as the key challenge in the design of an end-to-end smart grid. A multiagent system, with agents located at th

The Formation of Collective Silk Balls in the Spider Mite Tetranychus urticae Koch

Tetranychus urticae is a phytophagous mite that forms colonies of several thousand individuals. These mites construct a common web to protect the colony. When plants become overcrowded and food resources become scarce, individuals gather at the plant apex to form a ball composed of mites and their silk threads. This ball is a structure facilitating group dispersal by wind or animal transport. Until now, no quantitative study had been done on this collective form of migration. This is the first attempt to understand the mechanisms that underlie the emergence and growth of the ball. We studied this collective behaviour under laboratory conditions on standardized infested plants. Our results show that the collective displacement and the formation of balls result from a recruitment process: by depositing silk threads on their way up to the plant apex, mites favour and amplify the recruitment toward the balls. A critical threshold (quorum response) in the cumulative flow of mites must be reached to observe the emergence of a ball. At the beginning of the balls formation, mites form an aggregate. After 24 hours, the aggregated mites are trapped inside the silk balls by the complex network of silk threads and finally die, except for recently arrived individuals. The balls are mainly composed of immature stages. Our study reconstructs the key events that lead to the formation of silk balls. They suggest that the interplay between mites' density, plant morphology and plant density lead to different modes of dispersions (individual or collective) and under what conditions populations might adopt a collective strategy rather than one that is individually oriented. Moreover, our results lead to discuss two aspects of the cooperation and altruism: the importance of Allee effects during colonization of new plants and the importance of the size of a founding group

Bandwidth management for the people

In the context of a rapidly growing broadband market, it is critical to understand the expectations and quality of service requirements of a changing population of end users, in order to make informed strategic decisions. Although a number of technologies are available to fine-tune bandwidth allocation and ensure various forms of ‘fairness’, the performance, cost and marketing implications of choosing one regime over another are not always obvious to decision-makers. In this paper, we present the broadband broker (B-Cube) simulation tool and demonstrate how it can be used as a strategic planning tool to identify and evaluate the advantages and shortcomings of a wide variety of broadband products, bandwidth management schemes or changes in usage patterns. The main difference between B-Cube and other tools is that using it only requires an understanding of the top-level principles governing the distribution of the limited broadband resource

Focusing attention in populations of semi-autonomously operating sensing nodes

Cognition and the cognitive processing of sensory information in biological entities is known to occur over multiple layers of processing. In the example of human vision there are a vast number of photo-receptors feeding into various layers of cells which pre-process the original information before it arrives to the brain (as biased data).We propose to use a mechanism known to theoretical biologists as a means to bring about adaptive selforganization in colonies of social insects, and to apply it to such early stage signal processing. The underlying mathematical model is simple, and in the coming years, robotics will move into an era when aggregating simple computation devices into massively large collectives becomes feasible, making it possible to actually build such distributed cognitive sensing systems

Scale-free topology for pervasive networks

Scale-free graphs and their properties have attracted considerable interest over the last 4–5 years, after it was discovered that many natural and artificial networks belong to this category. However, the so-called ‘preferential attachment rule’, whereby scale-free topology can most easily be obtained, relies on newcomers having a global knowledge of the existing connectivity profile. Moreover, the addition of new nodes is usually assumed to be sequential and monotonous (one new node joins the network between two consecutive updates of the global connectivity profile, throughout the growth process). This is incompatible with the requirements of pervasive, ad hoc systems, where it cannot be guaranteed that either of these conditions applies. In this paper, we investigate methods to overcome this difficulty by devising realistic connection protocols that would allow approximating scale-free topology on the sole basis of local information exchange. We argue that successful implementation of our findings could have important implications for pervasive computing environments, as scale-free topology has very desirable features in terms of efficiency and robustness

Optimisation of ICT Infrastructure and Energy Efficiency Techniques in Next Generation Internet

Increasing customer requirements for 'always-on'connectivity brings with it increased energy consumption across any ICT infrastructure. The growth in multimedia applications, social computing and on-demand streaming services is driving the deployments of Next Generation Networks by network operators in support of service providers. Coupled to this is the increased awareness of the need to reduce the carbon footprint of maintaining the communications infrastructure and companies are now exploring methods and protocols to embed more energy efficient components, protocols, and optimisation technologies within their infrastructures. In this paper several energy efficiency techniques are reviewed, and their potential impact is discussed. An initial simple model for calculating the savings to be gained is presented

Applying Self-Aggregation to Load Balancing: Experimental Results

One of the today issues in software engineering is to find new effective ways to deal intelligently with the increasing complexity of distributed computing systems. In this context a crucial role is played by the balancing of the work load among all nodes in the system. So far load balancing approaches have been designed for networks with fixed or dynamic topologies. These approaches work well in the case each node knows its similes and is able to contact them to delegate tasks. However, they do not address the needs of more dynamic systems where nodes are able to process different types of jobs and have limited knowledge about their neighbors and the whole system. To address these issue, we are experimenting with the usage of autonomic self-aggregation techniques that rewire such highly dynamic systems in groups of homogeneous nodes that are then able to balance the load among each others. We present our approach and show through simulation that it provides significant advantages under the circumstances described before