148 research outputs found

    ptp++: A Precision Time Protocol Simulation Model for OMNeT++ / INET

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    Precise time synchronization is expected to play a key role in emerging distributed and real-time applications such as the smart grid and Internet of Things (IoT) based applications. The Precision Time Protocol (PTP) is currently viewed as one of the main synchronization solutions over a packet-switched network, which supports microsecond synchronization accuracy. In this paper, we present a PTP simulation model for OMNeT++ INET, which allows to investigate the synchronization accuracy under different network configurations and conditions. To show some illustrative simulation results using the developed module, we investigate on the network load fluctuations and their impacts on the PTP performance by considering a network with class-based quality-of-service (QoS) support. The simulation results show that the network load significantly affects the network delay symmetry, and investigate a new technique called class probing to improve the PTP accuracy and mitigate the load fluctuation effects.Comment: Published in: A. F\"orster, C. Minkenberg, G. R. Herrera, M. Kirsche (Eds.), Proc. of the 2nd OMNeT++ Community Summit, IBM Research - Zurich, Switzerland, September 3-4, 201

    Spare capacity allocation using shared backup path protection for dual link failures

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    This paper extends the spare capacity allocation (SCA) problem from single link failure [1] to dual link failures on mesh-like IP or WDM networks. The SCA problem pre-plans traffic flows with mutually disjoint one working and two backup paths using the shared backup path protection (SBPP) scheme. The aggregated spare provision matrix (SPM) is used to capture the spare capacity sharing for dual link failures. Comparing to a previous work by He and Somani [2], this method has better scalability and flexibility. The SCA problem is formulated in a non-linear integer programming model and partitioned into two sequential linear sub-models: one finds all primary backup paths first, and the other finds all secondary backup paths next. The results on five networks show that the network redundancy using dedicated 1+1+1 is in the range of 313-400%. It drops to 96-181% in 1:1:1 without loss of dual-link resiliency, but with the trade-off of using the complicated share capacity sharing among backup paths. The hybrid 1+1:1 provides intermediate redundancy ratio at 187-310% with a moderate complexity. We also compare the passive/active approaches which consider spare capacity sharing after/during the backup path routing process. The active sharing approaches always achieve lower redundancy values than the passive ones. These reduction percentages are about 12% for 1+1:1 and 25% for 1:1:1 respectively

    On Security and Reliability using Cooperative Transmissions in Sensor Networks

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    Recent work on cooperative communications has demonstrated benefits in terms of improving the reliability of links through diversity and/or increasing the reach of a link compared to a single transmitter transmitting to a single receiver (single-input single-output or SISO). In one form of cooperative transmissions, multiple nodes can act as virtual antenna elements and provide such benefits using space-time coding. In a multi-hop sensor network, a source node can make use of its neighbors as relays with itself to reach an intermediate node, which will use its neighbors and so on to reach the destination. For the same reliability of a link as SISO, the number of hops between a source and destination may be reduced using cooperative transmissions. However, the presence of malicious or compromised nodes in the network impacts the use of cooperative transmissions. Using more relays can increase the reach of a link, but if one or more relays are malicious, the transmission may fail. In this paper, we analyze this problem to understand the conditions under which cooperative transmissions may fare better or worse than SISO transmissions

    A Framework of Efficient Hybrid Model and Optimal Control for Multihop Wireless Networks

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    The performance of multihop wireless networks (MWN) is normally studied via simulation over a fixed time horizon using a steady-state type of statistical analysis procedure. However, due to the dynamic nature of network connectivi- ty and nonstationary traffic, such an approach may be inap- propriate as the network may spend most time in a transien- t/nonstationary state. Moreover, the majority of the simu- lators suffer from scalability issues. In this work, we presents a performance modeling framework for analyzing the time varying behavior of MWN. Our framework is a hybrid mod- el of time varying connectivity matrix and nonstationary network queues. Network connectivity is captured using s- tochastic modeling of adjacency matrix by considering both wireless link quality and node mobility. Nonstationary net- work queues behavior are modeled using fluid flow based differential equations. In terms of the computational time, the hybrid fluid-based model is a more scalable tool than the standard simulator. Furthermore, an optimal control strategy is proposed on the basis of the hybrid model

    Improving the Performance of Multi-Hop Wireless Networks by Selective Transmission Power Control

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    In a multi-hop wireless network, connectivity is determined by the link that is established by the receiving signal strength computed by subtracting the path loss from the transmission power. Two path loss models are commonly used in research namely two-ray ground and shadow fading, which determine the receiving signal strength and affect the link quality. Link quality is one of the key factors that affect network performance. In general, network performance improves with better link quality in a wireless network. In this study, we measure the connectivity and performance in a shadow fading path loss model, and our observations shows that both are severely degraded in this path loss model. To improve network performance, we propose power control schemes utilizing link quality to identify the set of nodes required to adjust the transmission power in order to improve the network throughput in both homogeneous and heterogeneous multi-hop wireless networks. Numerical studies to evaluate the proposed schemes are presented and compared.\ud \ud \ud \ud \ud \u

    Kosovo after the ICJ opinion

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    Mining Historical Data towards Interference Management in Wireless SDNs

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    WiFi networks are often planned to reduce interference through planning, macroscopic self-organization (e.g. channel switching) or network management. In this paper, we explore the use of historical data to automatically predict traffic bottlenecks and make rapid decisions in a wireless (WiFi-like) network on a smaller scale. This is now possible with software defined networks (SDN), whose controllers can have a global view of traffic flows in a network. Models such as classification trees can be used to quickly make decisions on how to manage network resources based on the quality needs, service level agreement or other criteria provided by a network administrator. The objective of this paper is to use data generated by simulation tools to see if such classification models can be developed and to evaluate their efficacy. For this purpose, extensive simulation data were collected and data mining techniques were then used to develop QoS prediction trees. Such trees can predict the maximum delay that results due to specific traffic situations with specific parameters. We evaluated these decision/classification trees by placing them in an SDN controller. OpenFlow cannot directly provide the necessary information for managing wireless networks so we used POX messenger to set up an agent on each AP for adjusting the network. Finally we explored the possibility of updating the tree using feedback that the controller receives from hosts. Our results show that such trees are effective and can be used to manage the network and decrease maximum packet delay

    Identifying Malicious Nodes in Multihop IoT Networks using Dual Link Technologies and Unsupervised Learning

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    Packet manipulation attack is one of the challenging threats in cyber-physical systems (CPSs) and Internet of Things (IoT), where information packets are corrupted during transmission by compromised devices. These attacks consume network resources, result in delays in decision making, and could potentially lead to triggering wrong actions that disrupt an overall system's operation. Such malicious attacks as well as unintentional faults are difficult to locate/identify in a large-scale mesh-like multihop network, which is the typical topology suggested by most IoT standards. In this paper, first, we propose a novel network architecture that utilizes powerful nodes that can support two distinct communication link technologies for identification of malicious networked devices (with typical singlelink technology). Such powerful nodes equipped with dual-link technologies can reveal hidden information within meshed connections that is hard to otherwise detect. By applying machine intelligence at the dual-link nodes, malicious networked devices in an IoT network can be accurately identified. Second, we propose two techniques based on unsupervised machine learning, namely hard detection and soft detection, that enable dual-link nodes to identify malicious networked devices. Our techniques exploit network diversity as well as the statistical information computed by dual-link nodes to identify the trustworthiness of resource-constrained devices. Simulation results show that the detection accuracy of our algorithms is superior to the conventional watchdog scheme, where nodes passively listen to neighboring transmissions to detect corrupted packets. The results also show that as the density of the dual-link nodes increases, the detection accuracy improves and the false alarm rate decreases

    On Security and reliability using cooperative transmissions in sensor networks

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    Cooperative transmissions have received recent attention and research papers have demonstrated their benefits for wireless networks. Such benefits include improving the reliability of links through diversity and/or increasing the reach of a link compared to a single transmitter transmitting to a single receiver (single-input single-output or SISO). In one form of cooperative transmissions, multiple nodes can act as virtual antenna elements and provide diversity gain or range improvement using space-time coding. In a multi-hop ad hoc or sensor network, a source node can make use of its neighbors as relays with itself to reach an intermediate node with greater reliability or at a larger distance than otherwise possible. The intermediate node will use its neighbors in a similar manner and this process continues till the destination is reached. Thus, for the same reliability of a link as SISO, the number of hops between a source and destination may be reduced using cooperative transmissions as each hop spans a larger distance. However, the presence of ma-licious or compromised nodes in the network impacts the benefits obtained with cooperative transmissions. Using more relays can increase the reach of a link, but if one or more relays are malicious, the transmission may fail. However, the relationships between the number of relays, the number of hops, and success probabilities are not trivial to determine. In this paper, we analyze this problem to understand the conditions under which cooperative transmissions fare better or worse than SISO transmissions. We take into consideration additional parameters such as the path-loss exponent and provide a framework that allows us to evaluate the conditions when cooperative transmissions are better than SISO transmissions. This analysis provides insights that can be employed before resorting to simulations or experimentation. © Springer Science+Business Media, LLC 2012
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