Encoding of Functions of Correlated Sources

This submission is being withdrawn due to serious errors in the achievability proofs. The reviewers of the journal I had submitted to had found errors back in 2006. I had forgotten about this paper until I saw the CFP for a JSAC issue on in-network computation. http://www.jsac.ucsd.edu/Calls/in-networkcomputationcfp.pdf.Comment: This paper has been withdraw

Achieve Better Ranking Accuracy Using CloudRank Framework for Cloud Services

Building high quality cloud applications becomes an urgently required research problem. Nonfunctional performance of cloud services is usually described by quality-of-service (QoS). In cloud applications, cloud services are invoked remotely by internet connections. The QoS Ranking of cloud services for a user cannot be transferred directly to another user, since the locations of the cloud applications are quite different. Personalized QoS Ranking is required to evaluate all candidate services at the user - side but it is impractical in reality. To get QoS values, the service candidates are usually required and it is very expensive. To avoid time consuming and expensive realworld service invocations, this paper proposes a CloudRank framework which predicts the QoS ranking directly without predicting the corresponding QoS values. This framework provides an accurate ranking but the QoS values are same in both algorithms so, an optimal VM allocation policy is used to improve the QoS performance of cloud services and it also provides better ranking accuracy than CloudRank2 algorithm.Comment: 6 pages, 10 figures, Published with International Journal of Engineering Trends and Technology (IJETT

Absolute semi-deviation risk measure for ordering problem with transportation cost in Supply Chain

We present a decomposition method for stochastic programs with 0-1 variables in the second-stage with absolute semi-deviation (ASD) risk measure. Traditional stochastic programming models are risk-neutral where expected costs are considered for the second-stage. A common approach to address risk is to include a dispersion statistic in addition with expected costs and weighted appropriately. Due to the lack of block angular structure, stochastic programs with ASD risk-measure possess computational challenges. The proposed decomposition algorithm uses another risk-measure `expected excess', and provides tighter bounds for ASD stochastic models. We perform computational study on a supply chain replenishment problem and standard knapsack instances. The computational results using supply chain instances demonstrate the usefulness of ASD risk-measure in decision making under uncertainty, and knapsack instances indicate that the proposed methodology outperforms a direct solver

Branch-and-price algorithm for an auto-carrier transportation problem

Original equipment manufacturers (OEMs) manufacture, inventory and transport new vehicles to franchised dealers. These franchised dealers inventory and sell new vehicles to end users. OEMs rely on logistics companies with a special type of truck called an auto-carrier to transport the vehicles to the dealers. The process of vehicle distribution has a common challenge. This challenge involves determining routes, and the way to load the vehicles onto each auto-carrier.In this paper, we present a heuristic to determine the route for each auto-carrier based on the dealers' locations, and subsequently, a branch-and-price algorithm to obtain optimal solutions to the loading problem based on the generated route. The loading problem considers the actual dimensions of the vehicles, and the restrictions imposed by vehicle manufacturers and governmental agencies on the loading process. We perform extensive computational experiments for the loading problem using real-world instances, and our results are benchmarked with a holistic model to corroborate the effectiveness of the proposed method. For the largest instance comprising of 600 vehicles, the proposed method computes an optimal solution for the loading problem within a stipulated runtime

Packet Score based network security and Traffic Optimization

One of the critical threat to internet security is Distributed Denial of Service (DDoS). This paper by the introduction of automated online attack classification and attack packet discarding helps to resolve the network security issue by certain level. The incoming packets are assigned scores based on the priority associated with the attributes and on comparison with probability distribution of arriving packets on per packet basis

Distributed Denial of Service (DDoS) Attacks Detection Mechanism

Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the router's resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host

Optimizing the Cost for Resource Subscription Policy in IaaS Cloud

Cloud computing allow the users to efficiently and dynamically provision computing resource to meet their IT needs. Cloud Provider offers two subscription plan to the customer namely reservation and on-demand. The reservation plan is typically cheaper than on-demand plan. If the actual computing demand is known in advance reserving the resource would be straightforward. The challenge is how to make properly resource provisioning and how the customers efficiently purchase the provisioning options under reservation and on-demand. To address this issue, two-phase algorithm are proposed to minimize service provision cost in both reservation and on-demand plan. To reserve the correct and optimal amount of resources during reservation, proposed a mathematical formulae in the first phase. To predict resource demand, use kalman filter in the second phase. The evaluation result shows that the two-phase algorithm can significantly reduce the provision cost and the prediction is of reasonable accuracy.Comment: 6 pages,8 figures,"Published with International Journal of Engineering Trends and Technology (IJETT)". M.Uthaya Banu, K.Saravanan. Article:Optimizing the Cost for Resource Subscription Policy in IaaS Clou

Detecting Linear Block Codes in Noise using the GLRT

In this paper, we consider the problem of distinguishing the noisy codewords of a known binary linear block code from a random bit sequence. We propose to use the generalized likelihood ratio test (GLRT) to solve this problem. We also give a formula to find approximate number of codewords required and compare our results with an existing method

A Pattern Recognition Approach To Secure Cipher Documents

Natural phenomena show that many creatures form large social groups and move in regular patterns. Previous In this paper, we first propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. Afterward, we propose a compression algorithm, called 2P2D, which exploits the obtained group movement patterns to reduce the amount of delivered data. The compression algorithm includes a sequence merge and an entropy reduction phases. we formulate a Hit Item Replacement (HIR) problem and propose a Replace algorithm that obtains the optimal solution. Moreover, we devise three replacement rules and derive the maximum compression ratio

Power Interference Modeling for CSMA/CA based Networks using Directional Antenna

In IEEE 802.11 based wireless networks adding more access points does not always guarantee an increase of network capacity. In some cases, additional access points may contribute to degrade the aggregated network throughput as more interference is introduced. This paper characterizes the power interference in CSMA/CA based networks consisting of nodes using directional antenna. The severity of the interference is quantized via an improved form of the Attacking Case metric as the original form of this metric was developed for nodes using omnidirectional antenna. The proposed metric is attractive because it considers nodes using directional or omnidirectional antenna, and it enables the quantization of interference in wireless networks using multiple transmission power schemes. The improved Attacking Case metric is useful to study the aggregated throughput of IEEE 802.11 based networks; reducing Attacking Case probably results in an increase of aggregated throughput. This reduction can be implemented using strategies such as directional antenna, transmit power control, or both.Comment: Submitted to Elsevier's Journal of Computer Communications, 40 pages, 17 figures and 25 reference