A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Quality of support for multicasting over mobile ad-hoc networks

An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background: Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability. Methods: In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues. Results: The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs. Conclusion: In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

Truthful and Quality Conscious Query Incentive Networks

Query incentive networks capture the role of incentives in extracting information from decentralized information networks such as a social network. Several game theoretic tilt:Kids of query incentive networks have been proposed in the literature to study and characterize the dependence, of the monetary reward required to extract the answer for a query, on various factors such as the structure of the network, the level of difficulty of the query, and the required success probability.None of the existing models, however, captures the practical andimportant factor of quality of answers. In this paper, we develop a complete mechanism design based framework to incorporate the quality of answers, in the monetization of query incentive networks. First, we extend the model of Kleinberg and Raghavan [2] to allow the nodes to modulate the incentive on the basis of the quality of the answer they receive. For this qualify conscious model. we show are existence of a unique Nash equilibrium and study the impact of quality of answers on the growth rate of the initial reward, with respect to the branching factor of the network. Next, we present two mechanisms; the direct comparison mechanism and the peer prediction mechanism, for truthful elicitation of quality from the agents. These mechanisms are based on scoring rules and cover different; scenarios which may arise in query incentive networks. We show that the proposed quality elicitation mechanisms are incentive compatible and ex-ante budget balanced. We also derive conditions under which ex-post budget balance can beachieved by these mechanisms.

A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

Clustering in Concept Association Networks

We view association of concepts as a complex network and present a heuristic for clustering concepts by taking into account the underlying network structure of their associations. Clusters generated from our approach are qualitatively better than clusters generated from the conventional spectral clustering mechanism used for graph partitioning.

Design of incentive compatible protocols for wireless networks: A game theoretic approach

In this thesis work, we design rigorous and efficient protocols/mechanisms for different types of wireless networks using a mechanism design [1] and game theoretic approach [2]. Our work can broadly be viewed in two parts. In the first part, we concentrate on ad hoc wireless networks [3] and [4]. In particular, we consider broadcast in these networks where each node is owned by independent and selfish users. Being selfish, these nodes do not forward the broadcast packets. All existing protocols for broadcast assume that nodes forward the transit packets. So, there is need for developing new broadcast protocols to overcome node selfishness. In our paper [5], we develop a strategy proof pricing mechanism which we call immediate predecessor node pricing mechanism (IPNPM) and an efficient new broadcast protocol based on IPNPM. We show the efficacy of our proposed broadcast protocol using simulation results.

An efficient pricing based protocol for broadcasting in wireless ad hoc networks

In many applications of wireless ad hoc networks, wireless nodes are owned by rational and intelligent users. In this paper, we call nodes selfish if they are owned by independent users and their only objective is to maximize their individual goals. In such situations, it may not be possible to use the existing protocols for wireless ad hoc networks as these protocols assume that nodes follow the prescribed protocol without deviation. Stimulating cooperation among these nodes is an interesting and challenging problem. Providing incentives and pricing the transactions are well known approaches to stimulate cooperation. In this paper, we present a game theoretic framework for truthful broadcast protocol and strategy proof pricing mechanism called Immediate Predecessor Node Pricing Mechanism (IPNPM). The phrase strategy proof here means that truth revelation of cost is a weakly dominant-strategy (in game theoretic terms) for each node. In order to steer our mechanism-design approach towards practical implementation, we compute the payments to nodes using a distributed algorithm. We also propose a new protocol for broadcast in wireless ad hoc network with selfish nodes based on IPNPM. The features of the proposed broadcast protocol are reliability and a significantly reduced number of packet forwards compared to the number of network nodes, which in turn leads to less system-wide power consumption to broadcast a single packet. Our simulation results show the efficacy of the proposed broadcast protocol.

QoS with selfish nodes in wireless networks

The IEEE 802.1le medium access control (MAC) standard provides distributed service differentiation or Quality-of- Service (QoS) by employing a priority system. In 802.1 le networks, network traffic is classified into different priorities or access categories (ACs). Nodes maintain separate queues for each AC and packets at the head-of-line (HOL) of each queue contend for channel access using AC-specific parameters. Such a mechanism allows the provision of differentiated QoS where high priority, performance sensitive traffic such as voice and video applications will enjoy less delay, greater throughput and smaller loss, compared to low priority traffic (e. g. file transfer). The standard implicitly assumes that nodes are honest and will truthfully classify incoming traffic into its appropriate AC. However, in the absence of any additional mechanism, selfish users can gain enhanced performance by selectively classifying low priority traffic as high priority, potentially destroying the QoS capability of the system.

Neural network approach for fault location in unbalanced distribution networks with limited measurements

This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

Locant: A nature inspired location service for ad hoc networks

An efficient location service is a prerequisite to any robust, effective and precise location information aided Mobile Ad Hoc Network (MANET) routing protocol. Locant, presented in this paper is a nature inspired location service which derives inspiration from the insect colony framework, and it is designed to work with a host of location information aided MANET routing protocols. Using an extensive set of simulation experiments, we have compared the performance of Locant with RLS, SLS and DLS, and found that it has comparable or better performance compared to the above three location services on most metrics and has the least overhead in terms of number of bytes transmitted per location query answered.