A Service-Transparent and Self-Organized Optical Network Architecture

A distributed collaborative system based on grid services is proposed in this paper to support collaborative designing and manufacturing of products. The base of this system is an abstract model of collaborative designing and manufacturing. Resources are encapsulated into service objects and then the integration and sharing of these distributed heterogeneous resources are realised by using service proxy and open grid services architecture (OGSA). Services and interfaces of resources are described by extensible markup language (XML). The publishing and discovery of services are realised by utilising standardisation rule and similar vector matching technology. Lastly, the practicality of this system is validated by its application in the designing and manufacturing process of a product.

In this paper, we address the issue of the presence of malicious and selfish nodes in Vehicular Ad Hoc Networks (VANETs). Malicious nodes spread false and forged messages, while selfish nodes only cooperate for their own interest. To deal with this, we propose DTM <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , a Distributed Trust Model inspired by Spence's Job Market model from Economics. In our model, a sender node transmits a signal with its message. This signal represents a guarantee of the truthfulness of the message for the potential receivers. In order to use the signal, the sender node has to pay a cost, which depends on the value of the signal and its own behavior. Therefore, the worse the behavior of the sender node, the more expensive the signal cost. This model deters the sender nodes from acting as malicious nodes. Similarly, cooperation of the sender nodes is rewarded proportionally to the signal's value. We validated DTM <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> via extensive simulation in an urban scenario. We show that our approach is able to detect and evict gradually all malicious nodes in a network composed of 25%, and 50% of them. Moreover, our solution greatly decreases the ratio of corrupted and false data sent through a network to levels as low as 0%, and it increases the participation ratio of selfish nodes by 20%.

Servers in data center networks handle heterogenous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TA-ASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.

In Grid computing, resource management and fault tolerance services are important issues. The availability of the selected resources for job execution is a primary factor that determines the computing performance. The failure occurrence of resources in the grid computing is higher than in a tradition parallel computing. Since the failure of resources affects job execution fatally, fault tolerance service is essential in computational grids. And grid services are often expected to meet some minimum levels of quality of service (QoS) for desirable operation. However Globus toolkit does not provide fault tolerance service that supports fault detection service and management service and satisfies QoS requirement. Thus this paper proposes fault tolerance service to satisfy QoS requirement in computational grids. In order to provide fault tolerance service and satisfy QoS requirements, we expand the definition of failure, such as process failure, processor failure, and network failure. And we propose resource scheduling service, fault detection service and fault management service and show implement and experiment results.

Modeling a multi-queue network node with a fuzzy predictor

Framework based on communicability to measure the similarity of nodes in complex networks

An evolution model of KAD Dynamic Model Network (KDMN) is proposed to study the reason of hot node and simulate the process of network evolution based on node behavior from a holistic perspective. First, some symbols and meanings are introduced to describe nodes relationship and network states at a time step. Second, some evolution rules for network are formulated when node behaviors of join, exit, routing table update, data retrieval and content index distribution happen with different contextual scene in KAD network. In addition, a lightweight simulator is designed to implement the KDMN model. Moreover, an example of how to use the simulator to simulate the network changes in order to observe the result is described in detail. Finally, the KDMN is applied to analyze the reason for the formation of hot nodes in the BT and eMule network in the experiment. The different evolution principles of local priority, global priority and hybrid random are adopted based on the provision of network protocol of BT and eMule. The result of this experiment demonstrates that there are some hot nodes exist in the KAD network. However, the principle of hybrid random can effectively alleviate the phenomenon that a node is widely linked with others compared with global and local priority.

This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.

This paper deals with large, distributed real-time systems that have execution times and resource utilizations which cannot be characterized a priori. (The motivation for our work is provided in part by the characteristics of combat systems.) There are several implications of these characteristics: 1) demand space workload characterizations may need to be determined a posteriori, and 2) an adaptive approach to resource allocation may be necessary to accommodate dynamic workload changes. Thus, we present a scheme for dynamically managing distributed computing resources by continuously computing and assessing QoS and resource utilization metrics that are determined a posteriori. Specifically, the paper presents an adaptive distributed system reference architecture that is suitable for such an approach. This reference architecture provides the capabilities and infrastructure needed to construct multi-component, replicated, distributed object real-time systems that negotiate for a given level of QoS from the underlying distributed computing resources.KeywordsExecution TimeLoad SharingReference ArchitectureCombat SystemResource Management ServiceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In Wireless Ad-hoc Networks, nodes co-operate among themselves to forward data packets from a source node to a destination node. Nodes may participate in route discovery or route maintenance process but refuse to forward packets due to presence of faulty hardware or software or to save their resources, such as, battery power and bandwidth. Detection and isolation of misbehavior nodes are important issues to improve the quality of communication service and to save resources of well behaving wireless nodes. In this work, firstly, a neighbor Overhearing based Misbehavior Detection(OMD) scheme is proposed. In OMD, each node overhears the transmissions of its neighbors and calculates packet forwarding ratio of its own as well as its neighbors. Source node uses the calculated information to identify a misbehaving node. Secondly, an Autonomous Agent based Misbehavior Detection( AAMD) technique is proposed. In AAMD, past behavior of nodes in the network is used as a metric to calculate the selection probability of a node. An agent residing at a node is activated using the activation key generated by a trusted third party to verify the misbehavior of the node. The proposed schemes reduce communication overheads and identification delays to detect misbehaving nodes in wireless ad-hoc network. Simulation results are presented to evaluate the performance of the proposed OMD and AAMD schemes.

Spatial re-use TDMA (STDMA) is a medium access control (MAC) protocol which allows multiple transmitter-receiver pairs to communicate simultaneously, as long as they do not interfere too much with each other. Node and link assignment strategies for spatial re-use TDMA networks have previously been studied independently. The metric chosen in these studies is the uniform capacity, the minimum rate at which any node can communicate with any other node in the network. It has been shown that for large frame lengths, node assignment leads to lower spatial re-use than link assignment, resulting in lower uniform capacity than link assignment. In this paper, we first explore the behaviour of node and link assignment at small frame lengths. We show that node assignment achieves non-zero throughput values at lower frame lengths than link assignment, and that it outperforms link assignment at small frame lengths. This motivates the need for an assignment strategy that performs well for all values of the frame length. We propose a joint node-link assignment strategy and show that it performs as well as node assignment at small frame lengths and as well as link assignment at large frame lengths, while exceeding the performance of both node and link assignment at intermediate frame lengths.

Urban intermodality is an increasing phenomenon and nowadays modal choice nodes, nodes within urban networks from which it is possible to reach other nodes by using different transportation modalities, play a very important role in the analysis of passenger mobility. Therefore, the need of evaluating the performance of such nodes with the aim of making more convenient multimodal paths is described in this paper. The paper focuses on the problem of determining the attractive capacity of modal choice nodes in urban networks; the goal is to identify those nodes that could be attractive poles for modal exchanges and become location of new services, such as parking places, bus stops and informative panels. Starting from relevant Origin – Destination (O-D) paths that are derived from the demand of mobility, the paper analyzes the possible intermodal nodes by evaluating the role that such nodes play within urban networks on the basis of some structural attributes of the network itself. Inspired by the gravitational models, that are more generally used in the competitive location problems, we determine the attractive capacity of the well performing previously selected intermodal nodes; the aim is to verify whether the good behavior of the modal choice nodes inside the transportation network is also perceived by users. We report on some data related to the city of Genoa that for its topological and geographical structure and the wide offer of the public transportation system is well suited for intermodality.

This session deals with fundamental issues arising in wireless networking and their implications for high performance business, consumer and military computing applications. We will describe the physical basis for wireless networking, mobile IP solutions and challenges as well as ongoing research efforts to make high performance and high confidence computing over wireless networks possible.One of the major technical challenges for wireless computing is the volatility of the network links and nodes. Bandwidth and latency vary much more rapidly than in wired networks and network connectivity is highly intermittent because of transmission anomolies and power conservation, among other factors. Moreover, the network topology is constantly changing because the nodes are mobile.These challenges can be met using a variety of novel network management ideas and applications software. We are developing support for scalable mobile IP, dynamic network sensing and predictive routing, proxy servers and docking systems. Many of these developments use mobile agents as a building block. The mobile agent system we are using is based on Agent Tcl which was developed at Dartmouth (see http://www.cs.dartmouth.edu/ agent).Part of the research presented is funded by the US Department of Defense through a Multidisciplinary University Research Initiative at Dartmouth with subcontracts to Harvard, University of Illinois, RPI, Lockheed Martin and Al-phatech. Industrial partners include Merrill Lynch, Northern Telecom, Digital Equipment, Lucent and AT&T.

Wireless Sensor Networks (WSNs) being an indispensable entity of the Internet of Things (IoT) are found to be more and more widely utilized for the rapid advent of IoT environment. The reliability of data dissemination in the IoT environment completely depends on the secure neighbor discovery mechanism that are utilized for effective and efficient communication among the sensor nodes. Secure neighbor discovery mechanisms that significantly determine trustworthy sensor nodes are essential for maintaining potential connectivity and sustaining reliable data delivery in the energy-constrained self organizing WSN. In this paper, Fuzzy Technique of Order Preference Similarity to the Ideal Solution (TOPSIS)-based Secure Neighbor Discovery Mechanism (FTOPSIS-SNDM) is proposed for estimating the trust of each sensor node in the established routing path for the objective of enhancing reliable data delivery in WSNs. This proposed FTOPSIS-SNDM is proposed as an attempt to integrate the merits of Fuzzy Set Theory (FST) and TOPSIS-based Multi-criteria Decision Making (MCDM) approach, since the discovery of secure neighbors involves the exchange of imprecise data and uncertain behavior of sensor nodes. This secure neighbor is also influenced by the factors of packet forwarding potential, delay, distance from the Base Station (BS) and residual energy, which in turn depends on multiple constraints that could be possibly included into the process of secure neighbor discovery. The simulation investigations of the proposed FTOPSIS-SNDM confirmed its predominance over the benchmarked approaches in terms of throughput, energy consumption, network latency, communication overhead for varying number of genuine and malicious neighboring sensor nodes in network.

The paper considers grid computing systems with star architectures in which the resource management system (RMS) divides service tasks into subtasks, and sends the subtasks to different specialized resources for execution. To provide the desired level of service reliability, the RMS can assign the same subtasks to several independent resources for parallel execution. Some subtasks cannot be executed until they have received input data, which can be the result of other subtasks. This imposes precedence constraints on the order of subtask execution. The service reliability & performance indices are introduced, and a fast numerical algorithm for their evaluation given any subtask distribution is suggested. Illustrative examples are presented