In emergency healthcare situations, both time and connectivity represent critical factors in the efficiency of the emergency process. The quick transportation of the patient and the synchronization with the target hospital help save lives and avoid complications during the route. While traditional emergency routing systems typically prioritize shortest path algorithms, they often overlook an important dimension in today’s connected world: the stability of mobile communication throughout the transit process. In this paper, we propose a smart, urgency-sensitive emergency routing approach in Internet of Vehicles (IoV) environments, which selects emergency routes depending on both the travel time and the communication quality constraints. Our solution integrates real-time network metrics such as signal strength and latency measurements into the route decision-making process, ensuring uninterrupted data transmission between moving emergency vehicles and hospital systems. Optimization is based on the Reference-Point-Based NSGA-II genetic algorithm and compared to the classical routing process. Results demonstrate that our approach favors slightly longer but better-connected routes, significantly improving the reliability of patient data streaming during emergency situations, and is computationally feasible for real-time EMS deployment.

In recent years, mobility has become one of the most important aspects of all networks, including multi-controller SDMNs. Once authenticated, mobile users must be able to move freely between domains without losing access to the provided network services. To this aim, once authenticated, mobile users must be able to re-authenticate every time they move from their original domains. In this study, we present a novel 5G access authentication protocol designed specifically for multi-controller SDMN environments. The paper elaborates on the initial authentication procedure as well as the re-authentication process inherent to this protocol. In our proposed protocol the mobile user will not need to reach the authentication server for the re-authentication process. It provides the controller with its MSK token allowing him to approve the re-authentication request if the MSK token is valid. This will generate low latency improvement in terms of handover time. A comprehensive analysis is conducted to assess the robustness of the proposed authentication mechanism against diverse cyber attacks. Furthermore, an analytical equation for quantifying the communication costs involved in both the initial authentication and subsequent re-authentication processes is provided. In addition, to validate the security robustness of the proposed 5G access authentication protocol, we utilize the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool.

In today's fast-paced business environment, the value of a smart supply chain cannot be overstated. Numerous economic crises over the past few years have wreaked devastation on numerous businesses. Basic duties such as ensuring that products are available to customers and that the manufacturing facility has enough raw materials to maintain operations were central to the work of supply chain managers. However, as a result of rapid advances in creating logistics software, supply chain management has evolved into a complex procedure focused on forecasting demand, forming profitable alliances, and increasing operational effectiveness.This paper presents the performance and the benefits of applying smart supply chain management within cloud and IoT environment.

Routing packets efficiently is the main purpose of today’s networking. Mainly, efficiency deals with how securely are packets delivered taking in consideration the exponential growth of network threats, particularly the Distributed Denial of Service (DDoS) Attacks. However, security and routing are separately addressed in literature and little work was devoted to security-aware routing.In this paper, we point out the need to merge security and routing in SDN instead of addressing them separately. We propose a new DDoS-aware routing scheme using a cross-layer knowledge transfer between flows and switches. This scheme consists of learning features from flow-based DDoS attack datasets then transferring knowledge to switches. Transferred knowledge is used to establish reliable paths between end-points that avoid suspicious switches. Mainly, evaluation of a switch risk is based on a computation of a Suspicion Risk Factor (SRF) using a set of features learned from an ML-based classification of flows. Finally, SRFs of switches are used to seek for DDoS-aware paths. Evaluation results and analysis show that the proposed scheme outperforms the baseline protocol OSPF in terms of finding the most secure path and offered throughput.

With the emergence of cloud robotics, computation offloading presents a new trend in cloud computing that has been applied to robots; to provide them with resources for performing computationally intensive tasks. In most scientific research, the main objectives behind computation offloading are reducing energy consumption and minimizing the execution time of robotics applications. However, these two metrics are conflicting, and optimizing them simultaneously is challenging. Reducing energy consumption may lead to a rise in the completion time, and vice-versa. In this paper, we consider the problem of optimization of energy consumption and completion time in a cloud robotic system. We formulated the offloading decision as a multi-objective optimization problem. We further adapted the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find a set of Paretooptimal solutions. Through simulations, we demonstrated that our offloading solution can save 80% of the robot’s energy consumption; and reduce 70% of the application completion time. We proved also the adaptability of the model against bandwidth changes.

Cloud computing faces many challenges which constitute research problems. The key challenge is to achieve good resource management that will result in minimum energy consumption. This problem has been the subject of extensive research. In this paper, we report major solutions to the existing work proposed for the infrastructure cloud. We categorize these solutions based on approach optimization, used methods, and objective models. The latter are introduced by mathematical formulations that may be classified as mono-objective and multi-objective formulations. Typically, the single objective takes into account energy. Whereas, the multi-objective considers others, like resource utilization. Extensive simulation, using cloudsim, shows that the multi-objective formulations provide significant improvement than the mono-objective ones. Indeed, the results show an improvement of as much as 12% in the average energy consumption and 15% in the average resource utilization.

Cloud robotics is incessantly gaining ground, especially with the rapid expansion of wireless networks and Internet resources. In particular, computation offloading is emerging as a new trend, enabling robots with more powerful computation resources. It helps them to overcome the hardware and software limitations by leveraging parallel computing capabilities and the availability of large amounts of resources in the cloud. However, the performance gain of computation offloading in cloud robotics is still an ongoing research problem because of the conflicting factors that affect the performance. In this paper, we investigate this issue and we design a distributed cloud robotic architecture for computation offloading based on Kafka middleware as messaging broker. We experimentally validated our solution and tested its performance using image processing algorithms. Experimental results show a significant reduction in robot CPU load, as expected, with an increase in robot communication delays.

Virtual machine (VM) migration mechanism in data centers significantly improves the utilization of the server resource. While the recent work focuses on how to use VM migration to stability physical machine (PM) utilization or improve energy consumption, little attention has been agreed to network performance issues, such as architecture, link, load and inter-traffic between VMs in the data centers network (DCN) architectures. Network-aware Virtual Machine (NVM) placement and migration is developing as a very favorable technique for the optimization of compute network resource utilization, energy consumption, and network traffic minimization. Thus, NVM operation guarantees a fair share allocation of network resources, leading to a seamless VM mobility though decreasing degradation of network performance.The focus of this paper is to present the impact of several network architectures and virtualisation on how to reduce the energy consumed by virtual machine migration. We introduce a simulation setting for energy aware employing Green-Cloud simulator. The simulator is designed to detect the details of the consumed energy by datacenter components such us VMs, PMs, servers, switches, and links. The simulation results gotten for three-tier, Debug and High speed architectures show the value of each system in employing power management schema through DNS and DVFS by applying voltage scaling and dynamic shutdown technics.

According to the cloud computing paradigm, cloud services make use of Virtual Machines (VMs) that are running on Physical Machines (PMs). A user consumes VMs that are hosted on PMs located at one or several data centers. Energy consumption of a data center is highly correlated with the number of active PMs. A data center relies on a placement algorithm to assign the required VMs on a minimum number of PMs in order to minimize energy consumption. In this paper, we propose a VM placement algorithm based on Particle Swarm optimization (PSO) meta-heuristics. As opposed to reported VM placements, which all seek to minimize either energy consumption or resource wastage, our proposed PSO algorithm seeks to maximize packing efficiency while minimizing energy consumption. Extensive simulation results show that our algorithm significantly produces better results when compared to suggested work. Indeed, the solutions obtained with our algorithm require a lower number of PMs, lower energy consumption and a better balanced utilization of PMs.

The IoT (Internet of Things) is defined as a global infrastructure for the information society, which provides advanced services by interconnecting physical or virtual objects through existing interoperable information and communication technologies in evolution. To note, the explosion of the number of smartphones and connections has created a new market with almost infinite opportunities. In 2016, 5.5 million objects are connected every day in the world. A number that could quickly reach billions, by 2020 [1]. Gartner predicts that 26 billion objects will be installed in 2020. Other evaluations consider that a human being would interact with 1,000 to 5,000 objects during a normal day. The market for connected objects could range from a few tens of billions to up to several thousand billion units. Among the vital components of IoT, we find wireless sensor networks. WSNs allow the representation of dynamic characteristics of the real world in the virtual world of the Internet. Nevertheless, the opening of these types of network to the Internet presents a serious problem stand point security. The introduction of intrusion detection mechanisms is essential to limit the various attacks that threaten the proper functioning of the networks. In this work, we propose a new intrusion detection model for Internet of Things, specifically for WSNs. This model relies on a geographic location check of the nodes to make sure that we communicate with the right node for each transaction. Subsequently, we proposed rules for detecting attacks. A mathematical model for trust calculating was proposed to update trust nodes values and eliminate malicious nodes. The simulation results were able to show the effectiveness of our model.

wireless sensor networks (WSNs) are finding application in numerous fields. For many of these applications, some or all of the sensor nodes are mobile. Mobility management in WSNs is a challenging and has been the subject of intensive research. In this paper, we propose an IP-based mobility management protocol named Fast handover Proxy Mobile IPv6 for Sensor networks (FPMIPv6-S). FPMIPv6-S provides network-based mobility support for 6LoWPAN WSN when a sensor node moves between two Personal Area Networks (PANs). It is an improved version of the PMIPv6 protocol proposed for mobility management in IPv6 networks. FPMIPv6-S messages are carried by RPL protocol. We integrated the FPMIPv6-S protocol in the NS-3 simulator and performed a thorough performance comparison of FPMIPv6-S and RPL. Simulation results of the proposed protocol shows significantly improved performance with respect to three QoS criteria: (1) the packet loss rate; (2) and the Throughput.

Internet of Things (IoT) applications are driving the world to be smart by providing limitless services with optimized time and resources. Security and safety are paramount to ensure the reliability of IoT applications. For this purpose, Intrusion Detection Systems (IDS) must be employed in order to discover the intrusions and to contain and possibly correct their impact on the network.Reported IDS are not feasible in the context of the IoT. On the one side, rule based IDS require excessive storage cost to save and update attack signatures and they cannot detect the unknown attacks. On the other side, behavioral based IDS are more feasible in the context of IoT but they fail to detect some known attacks.In this paper, a Fuzzy based IDS is proposed where the undesired behavior is expressed using fuzzy logic. Also, after determining the fuzzy values, the decision is filtered by the Base Station. The parameters' values that influence on the proposed approach are determined following extensive simulations. Analytical study and simulation results show that the proposal outperforms existing solutions.

Software Defined Networks (SDN) is a promising network paradigm that offers flexibility, efficiency and finegrained control over forwarding Elements (FE) by decoupling control and data planes. The forwarding decision is often made by the controller by managing flow table entries in the switches. Certainly, flow table management raises a lot of concerns and various schemes have been proposed such as the traditional Hopby-Hop Forwarding scheme. Studies have proved that this scheme may lead to performance degradation due to a huge control traffic and a massive flow table consumption. To reduce performance degradation, source routing was proposed. Unfortunately, this may also lead to significant bandwidth overhead, particularly in large-scale networks.This paper deals with the concept of source routing using MPLS labels. Basically, our scheme ensures flexibility and is suitable for application both in SD-LAN and SD-WAN by supporting various n-port switches (n ≥ 4). Using a MaxHop clustering algorithm, the network is divided into several sections. In each section, a trade-off between control traffic overhead, bandwidth overhead and flow table usage is achieved using a linear weighted scalarization of the Multi-Objective optimization problem. Finally, we present the θ-MOBO algorithm to be run by the controller. Simulation results show that the proposed scheme outperforms parallel solutions such as MPLS label-based forwarding [1] [2] and Hop-by-Hop forwarding [3] schemes in terms of the bandwidth overhead and flow rejection rate.

Vehicular Ad-hoc NETworks (VANETs) offer a diversity of applications related especially to safety and entertainment. During the non-emergency periods, various multimedia applications can be employed, in this paper we focus on ameliorating the quality of video streaming downloaded by a moving vehicle. During the transmission of the video stream-ing, the vehicle switches from one RSU to another and may affect the perceived quality of the video. To minimize the dis-ruption, handover latency must be held to minimum values. This paper presents a predictive handoff mechanism based on estimation of the quality of link of neighboring RSUs. The main goal in this research is to minimize the time of handoff by minimizing the time of looking for the next RSU. The proposed mechanism is called Predictive Handoff Mechanism for Video streaming in cloud-based urban Vanet (PHMVV) where it is defined based on vehicle and RSU positions, the distance be-tween them, an RSUtable containing information of neighbor-ing RSUs and the quality of link of each RSU. The experiment of (PHMVV) is conducted using a network simulator, NS-3. The results are compared to SNR-based handoff where the vehicle waits until a threshold value of the SNR to trigger a handoff and search a next RSU. Our proposed approach reveals significant improvements on perceived video quality (PSNR and MOS), end-to-end delay and jitter.

The need for energy-efficient routing and data gathering protocols in large-scale environments becomes very challenging. Hierarchical routing in WSNs is a very important topic. It has been widely investigated relative to energy efficiency based routing protocols. LEACH (Low Energy Adaptive Clustering Hierarchy algorithm) is the pioneering cluster routing protocol in WSNs. However, it is not suitable for large scale network and wireless channel conditions are ignored during packet forwarding. To address this issue, we proposed a novel multi-hop clustering cross layer protocol based on LEACH. It considers both the SNR of different links and the residual energy of sensor nodes. Simulation results in terms of the average energy consumption, the network lifetime and the Packet Delivery Ratio show clearly the outperformance of the proposed algorithm versus the conventional LEACH.

Wireless Multimedia Sensor Networks (WMSNs) have recently gained a great attention of the research community as potential solutions for wide range of applications. However, they are subject to strict constraints due to their limited energy, limited processing capacities in contrast to the huge video data rate to be transmitted. To tackle with this challenge, we investigate in this paper, various protocols dedicated to the WMSNs in each layer aiming to reduce the amount of video data using powerful video encoder or/and reduce the energy consumption by increasing the life cycle of each node and consequently the life cycle of the whole network. Specifically, we consider the protocols of the application, network, and MAC layers. We have used the NS-2 framework, in which we have added the H264 encoder and decoder as application layer protocol. We have used the IEEE 802.15.4 and the SMAC protocols for the MAC layer, and the AODV and the AOMDV for the network layer. The obtained results are evaluated by the dead nodes number, the energy consumption and the Peak Signal to Noise Ratio (PSNR) for the video decoding quality.

Maintenance is a core challenge in all routing protocols. The utilization of IPv6 for Low Power and Lossy Networks (6LowPAN) resulted in the recent standardization of a dedicated routing protocol called RPL (Routing Protocol for Low Power and Losy Neworks). In 6LowPAN, a critical challenge exists in decreasing packet loss under the stringent energy-efficiency mandate to increase network longevity. Moreover, the challenge of failed nodes/links, and operating in a lossy environment where connections require rapid maintenance, present significant challenges. Recent attempts at routing maintenance in RPL presented advancements in handling failures, yet under reactive mechanisms that respond to failures and attempt to reduce network down-time. In this paper we design and implement a proactive RPL (Pro-RPL) maintenance scheme that enables the network to selectively predict and mitigate failures before they impact network connectivity. In Pro-RPL we capitalize on a suffering index that is associated with RPL nodes, and monitors their tendency to result in a failure. This dynamic monitoring is decentralized in nature, and presents a conforming yardstick across RPL nodes, to eliminate overhead in implementation and potential control-traffic over the network. We evaluate the efficiency of Pro-RPL in reducing packet loss, energy consumption and extending network lifetime via extensive simulations with the Cooja Simulator over the Contiki OS.

Wireless Sensor Networks (WSN) have attracted much interest in the last decade. It opened a new range of applications such as large area monitoring including environmental monitoring, wildlife exploration, and real time patient medical data which is collected by using wireless sensors. The WSN provides the options of flexibilities and cost saving for patients and healthcare industries. At the same time, there is a growing concern about the hospitals' ability to provide effective care during disaster events. For these reasons, tools that automate patient monitoring have the potential to greatly improve efficiency and quality of health care. In hospitals, medical data sensors which monitor patients produce an increasingly large volume of real-time data. The transmission of this data through wireless networks in a hospital becomes a crucial problem because the medical information of an individual is highly sensitive. It must be kept private and secure. The purpose of this paper is to present our initial effort in building a flexible strategy to achieve secure data transmission in medical wireless sensor networks.

Routing has been considered as one of the most important issues in 6LoWPAN [22] networks. For this reason, the Internet Engineering Task Force (IETF) has proposed a routing protocol called RPL (Routing Protocol for Low Power and Lossy Networks). This paper presents a performance evaluation of the repair mechanisms of RPL with storing mode, using the Contiki simulation environment. Performance metrics of interest are repair time, packet loss and power consumption. We also study the sensitivity of these metrics to network size and node location.

Distributed wireless sensor network technologies have become one of the major research areas in healthcare industries due to rapid maturity in improving the quality of life. Medical Wireless Sensor Network (MWSN) via continuous monitoring of vital health parameters over a long period of time can enable physicians to make more accurate diagnosis and provide better treatment. The MWSNs provide the options for flexibilities and cost saving to patients and healthcare industries. Medical data sensors on patients produce an increasingly large volume of increasingly diverse real-time data. The transmission of this data through hospital wireless networks becomes a crucial problem, because the health information of an individual is highly sensitive. It must be kept private and secure. In this paper, we propose a security model to protect the transfer of medical data in hospitals using MWSNs. We propose Compressed Sensing + Encryption as a strategy to achieve low-energy secure data transmission in sensor networks.

Source authentication in multicast communication is essential and challenging requirement. In this paper we address the multicast stream authentication problem when the communication channel is under the control of an opponent who can drop, reorder or inject data. In such a network model, robustness against packet loss, packet overhead and computing efficiency are important parameters to be taken into account when designing a multicast source authentication mechanism. The proposed scheme is based on adaptive and multi-layer connected chain structure in addition to an efficient recovery information model. It adapts the redundancy chaining degree depending on the actual packet loss rate in the network. Our mechanism provides non-repudiation of the origin and tolerates packet loss with low communication overhead, low delay and buffer capacity on the receiver side. NS-2 simulations show significant improvements over mechanisms in the same category.

The Quality of Service (QoS) provisioning paradigm has become highly complicated due to the rising of networks complexity, heterogeneity and unpredictability. This complexity resulted in the need to satisfy stringent user's QoS requirements which depends generally on network capabilities. To deal with this complexity, an autonomic management of the global network seems to be mandatory. Indeed, autonomic network management can offer a new way to master end-to-end performances by providing self-* properties to networks. Self-* properties include self-optimization, self-organization, self-protection and many others. This paper proposes an autonomic and flexible end-to-end QoS provisioning scheme which is based on the per-hop classes of service discovery and its mapping to user's QoS requirements basing on the k-nearest neighbor algorithm (k-NN). Simulation results show that the proposed scheme significantly outperforms performances of parallel solutions such as the IntServ-over-Diffserv model and the EEAC-SV approach proposed in [14] with respect to the request delay bounds and the packet dropping ratio capability, respectively.

The problem of providing source authentication in Wireless Sensor Networks (WSNs) has been a roadblock to their large scale deployment, and is still in its infancy. In this paper, we present novel symmetric-key-based authentication schemes which exhibit low computation and communication authentication overhead. Our schemes are built upon the integration of a reputation mechanism, a Bloom filter, and a key binary tree for the distribution and updating of the authentication keys. Analytical evaluation of the proposed authentication schemes shows that the estimated average number of concatenated message authentication code in a packet from time 0 till time t is 4pt, with p is the probability that a key is corrupted. Our schemes are lightweight and efficient with respect to computation, communication and energy overhead.

Natively, Multi Protocol Label Switching (MPLS) allows LSP/Tunnel setup using a round trip model. This Model consists of sending a request message, like the PATH message in the Resource Reservation Protocol(RSVP), and standing for a response message, like the RESV message in RSVP, upon which required resources are reserved. Moreover, crossed routers do not participate in flows classification according to DiffServ Model, since this classification is stringent and is driven by the ingress node at network entry. This paper proposes a new flexible one-way model of the LSP/Tunnel setup in MPLS networks which are based on the mapping of incoming requests on flows admission using a Naive Bayes model and the weighted K-nearest neighbor algorithm. The proposed model is compared to parallel solutions such as the IntServ-over-Diffserv model, the classical model using RSVP-TE and the EEAC-SV approach proposed in [12]. Simulation results show that the new model outperforms other solutions with respect to the request delay bounds and the packet dropping ratio capability, respectively.

Internet Service providers offer today a variety of of audio, video and data services. Traditional approaches for quality assessment of video services were based on Quality of Service (QoS) measurement. These measurements are considered as performance measurement at the network level. However, in order to make accurate quality assessment, the video must be assessed subjectively by the user. However, QoS parameters are easier to be obtained than the QoE subjective scores. Therefore, some recent works have investigated objective approaches to estimate QoE scores based on measured QoS parameters. The main purpose is the control of QoE based on QoS measurements. This paper presents several solutions and models presented in the literature. We discuss some other factors that must be considered in the mapping process between QoS and QoE. The impact of these factors on perceived QoE is verified through subjective tests.

Technology advances and services of modern networks have noticeably complicated their management such that in the near future it will be almost unfeasible for human administrators to monitor them. To manage this complexity, IBM has proposed the autonomic paradigm with its four self-management properties. Autonomic computing/networking intends to design computing architecture capable to self-adapt its configuration and to self-optimize its performance depending on its state in order to fulfil high-level goals predefined by the human operator. In this research work, we introduce AutoXL, a cross-layer autonomic architecture. AutoXL adopts a Knowledge plane and a Policy plane. The Knowledge plane is responsible of the management of knowledge (local and network-wide) which enables an autonomic element to be self-aware of its environment. The Policy plane is responsible of managing policies guiding the autonomic element to achieve the predefined objectives. Furthermore, we propose guidelines for autonomic architectures evaluation.

This paper presents a new solution for inter-domain recovery within MPLS networks. The proposed mechanism is based on efficient collaboration between several entities called PCEs (Path Computation Elements). One PCE is designated at each domain. All PCEs should communicate in order to ensure suitable End-to-End(E2E) failure handling, recovery and restoration. Based on normative instructions described in the RFC 5298 and the Backward Recursive PCE-based Computation approach (BRPC) presented in RFC 5441, the new mechanism offers an opportunity to achieve E2E recovery using up-to-date information and giving a way to maintain correct network states with respect to intra-domain as well as inter-domain contexts, without care of heterogeneity and autonomy of crossed areas. Simulation results prove that, compared to existing E2E protection and on-demand backup path recovery mechanisms, the proposed solution is able to support, more efficiently, inter-domain recovery regardless of per-domains policies and rules, by ensuring lower recovery time, improved resources management and low packet loss/disorder bounds.

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks. The accuracy of link quality estimation greatly impacts the efficiency of these protocols. Therefore, a thorough experimental evaluation of link quality estimators (LQEs) is mandatory. This motivated us to build a benchmarking testbed-RadiaLE, that automates LQEs evaluation by analyzing their statistical properties. Our testbed includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for setting up and controlling the experiments and also for analyzing the collected data, allowing for LQEs evaluation. To demonstrate the usefulness of RadiaLE, we carried out a comparative performance study of a set of well-known LQEs.

Multicast communication is becoming the basis for a growing number of applications. Therefore, securing multicast communication is a strategic requirement for effective deployment of large scale business multi-party applications. One of the main issues in securing multicast communication is the source authentication service. We address the multicast stream authentication problem when the communication channel is under the control of an opponent who can drop, reorder or inject data. In such a network model, packet overhead and computing efficiency are important parameters to be taken into account when designing a multicast source authentication mechanism. In this paper we present an efficient multicast source authentication mechanism based on a multi-layer connected chain structure. Our mechanism tolerates packet loss and guarantees non-repudiation of multicast origin. Simulation results show significant improvements over mechanisms in the same category.

Wireless sensor networks (WSN) are being widely deployed in military, healthcare and commercial environments. Since sensor networks pose unique challenges, traditional security methods, commonly used in enterprise networks, cannot be directly applied. In particular, broadcast source authentication is a critical security service in wireless sensor networks since it allows senders to broadcast messages to multiple receivers in a secure way. Public-key cryptography based solutions such as Elliptic Curve Cryptography (ECC) and Identity Based Cryptography (IBC) have been proposed but they all suffer from severe energy depletion attacks, resulting from a high computational and communication overheads. In this paper, we present a novel symmetric-key-based authentication scheme that exhibits low broadcast authentication overhead and thus avoiding the problem flaws inherent to the public key cryptography based schemes. Our scheme is built upon the integration of multi-level μTesla protocol, staggered authentication and the Bloom Filter. We show that our authentication scheme is very efficient in terms of energy consumption related to both computation and communication.

Sharing of content on the internet has become more and more prevalent over the years. As the number of internet users grows exponentially, issues of scale related to content distribution and lookup have become more important. But, since both content and network node are assigned a unique identifier in the basic design of Distributed Hash Table (DHT), randomly hashed to a same id space, “locality-awareness” is not inherent due to the topology mismatching between the Peer-to-Peer overlay network and the physical underlying network. In this paper, we propose to incorporate physical locality onto nodes as well as semantic approach onto content into a Chord system. Initially, we incorporate network positioning model for capturing physical location information of network nodes. Secondly, we organize the data resources based on the domain of interest to route requests to the most likely physical location of data. For this reason, we incorporate GNP (Global Network Positioning) into Chord since peers can easily maintain geometric coordinates that characterize their locations in the Internet. Besides, we apply the Topic maps approach as a semantic layer in organizing resources based on the domain of interest on top of the Chord Protocol. The measured results show that Semantic-Chord-GNP efficiently locates the nearest available node by reducing the number of visited nodes as the overlay hop number. In addition, both the query latency and the the average success rate for content location when using Semantic-Chord-GNP are less than the basic algorithm of Chord.

Source authentication in multicast communication is essential and challenging requirement. We address the multicast stream authentication problem when the communication channel is under the control of an opponent who can drop, reorder or inject data. In such a network model, packet overhead and computing efficiency are important parameters to be taken into account when designing a multicast source authentication mechanism. The proposed scheme in this paper is highly robust to packet loss. It consists of a multi-layer connected chain structure in addition to an efficient recovery information model based on simple XOR operations. Our mechanism provides non-repudiation of the origin, low communication overhead, low delay and buffer capacity on the receiver side. NS-2 simulations show significant improvements over mechanisms in the same category.

Web cache replacement Algorithms proposed in the literature try to maximize the Hit Ratio (HR), the Byte Hit Ratio (BHR), and the Delay Saving Ratio (DSR). However, even with an infinite Web cache storage capacity, values of these metrics could not exceed 70% most of the time. This is due to the fact that, given a workload, the first reference to an object is always a miss. Moreover, a statistical analysis of the workload shows that as much as 76% of objects are One-Timers (OT), i.e. they are referenced only once. Caching OT objects usually degrade the performance of all Web cache replacement algorithms. In fact, it may cause the eviction of N-Timer (NT) objects and hence increases the number of misses. In this paper, we present a technique to classify whether a cached object is an OT or not. We show through simulation that classification may significantly enhance the performance of replacement algorithms with respect to the HR, the BHR and the DSR.

This paper proposes an improvement to the IETF (Internet Engineering Task Force) standard intra-domain recovery mechanisms based on a combination of the existing IETF standards. The proposed mechanism defines a new fast recovery process that ensures efficient resource utilization. Since the IETF protection switching mechanism follows a pre-planned approach, i.e., it selects a backup path only once at the LSP (Label Switched Path) setup time, it may not reflect the exact status of network resources at the time of a fault. Moreover, backup path computation may infer unsolicited delay before an available backup path can be selected. The proposed solution combines the pre-planned protection switching mechanism with an on-line computation of an available backup path that may be closer to the failing point. The backup path computation is ensured by an efficient and fast engine based on up-to-date network state and capability to support the required Forwarding Equivalence Class (FEC). Once found, a safe transition from protection model to the new backup path is performed. Simulations results prove that the proposed mechanism is able to ensure and maintain an optimized network state regardless of the fault occurrence.

In this paper, we focus on an equation based single rate TCP-Friendly Multicast Congestion Control (TFMCC) protocol, primarily proposed for wired networks. In TFMCC, the rate is determined as a function of packet loss ratio (PLR), round trip time (RTT) and packet size, where each receiver estimates its throughput at each RTT, using an equation that estimates the steady-state throughput of a TCP source. The multicast source adjusts its rate according to the slowest receiver (a.k.a. Current Limiting Receiver CLR), within the session. However, when this approach is applied in wireless networks, mobility related packet losses will cause frequent changes of the congestion representative. In this paper, we evaluate TFMCC in a wireless environment, while using an equation that models the steady state throughput of a multicast source controlled according to the AIMD (Additive Increase Multiplicative Decrease) approach. Another modification consists of monitoring RTT variations at the source side in order to predict any modifications at the CLR in relation to the network conditions. The source adjusts the sending rate according to the new selected CLR. Simulation results show that these modifications result in remarkable performance improvements with respect to throughput (increase by as much as 50%), time to react (reduction by as much as 25%), and magnitude of oscillations at the wireless nodes, without carrying any changes at the MAC layer.

Layer 2 and layer 1 VPN services, ranging from simple leased lines to extending private LANs, are commonplace today. However, with the continuously growing economic difficulties, capital meltdown and telecommunication business turmoil, delivering those VPN services at the lowest cost or with the maximum revenue margin, while committing to Service Level Agreements (SLA), has become essential. We show that whether we tackle the optimal VPN design problem from an Incumbent Local Exchange Carrier (ILEC) standpoint or from a Competitive Local Exchange Carrier (CLEC) standpoint, we obtain contradictory rules. We show that by building Edge Disjoint VPN trees and splitting the traffic among them, the ILEC can achieve maximum throughput, revenue, and better network performance. On the other hand, by concentrating all the VPN traffic over a single tree, the CLEC can minimize the cost of leased bandwidth while meeting minimum SLA targets. We then propose two simple algorithms that can help carriers and service provides leverage their networks and increase their revenue margins while committing to tight SLAs with their customers.

With the emergence of Metro Ethernet as a high speed and carrier grade technology across public networks, the support of Quality of Service (QoS) and Service Level Agreements (SLA) has become an essential feature of Ethernet. In such context, the issues of network security and data transfer delay are regaining significant importance. The IEEE has recently introduced the 802.1AE MACSec protocol which aims at providing hop by hop security but that does not guarantee end to end security across public networks. In order to provide end-to-end security, in general a higher layer security protocol such as IPSec would be required. In this paper we propose an enhancement to the MACSec protocol in order to maintain the advantages of providing security at layer 2 while assuring an end-to-end security; alleviating the need for higher layer security protocols. We show that our approach enhances network performance in terms of transfer delay and delay variation while providing security levels comparable to those delivered by the combination of IPSec and MACSec.

The provision of Quality of Service (QoS) over wireless networks has recently been the subject of intensive research. There is a growing consensus among the research community that combining cross-layering and autonomic paradigms is, until now, the best alternative for better QoS support in such networks. The cross-layer concept is recommended to over-come the performance problems of the wireless channel, and the autonomic concept is imposed as the size and complexity of networks grow. Most proposed cross-layer architectures lack of autonomicity. Moreover, the majority of them considers purely local information in their optimizations and do not care about the effects of such egoistic behavior on other wireless nodes. This non-collaborative behavior limits the overall system performance. We combine cross-layering and autonomic concepts in the design of a new architecture called XLEngine (Cross-Layer Engine) having the ability to make optimizations based on local and network wide knowledge. We implemented XLEngine under the simulator J-Sim. We show, through simulations, that our XLEngine architecture significantly outperforms the layered architecture.

This paper explores the perceptual effect of network delay jitters on consumers' quality of experience during packet-based VoIP conversations. Novel parametric speech quality models are proposed to faithfully capture speech quality impairment caused by network delay jitter and de-jittering buffer settings. The proposed models have been rigorously conceived following a regression analysis approach using a wide range of network delay jitter traces and de-jittering buffer settings. The network delay traces were synthetically produced by a stochastic generator, widely used by the research community. Moreover, new speech quality models, which quantify the individual and mixed perceptual effect of network random packet losses and delay jitter, are proposed and validated. The packet layer key parameters of proposed speech quality models, namely mean network delay jitter and de-jittering buffer delay, are easily accessible at run-time. Experimental results show that our no-reference speech quality models correlate very well with the standard full-reference speech quality models. Indeed, our performance evaluation shows correlation factors equal to 0.97 and 0.94 for, respectively, the G.711 and the G.729 CODECs. The proposed speech quality models should help design optimized schemes for network delay jitter removal, thus improving the perceptual speech quality for a given network delay jitter intensity. Moreover, the speech quality models can be used to accurately measure in a non-intrusive way the perceptual effect of network delay jitter and packet loss, separately. This constitutes a desirable feature, as it enables the smart mitigation of the sources of speech quality degradation.

Layer 2 and layer 1 VPN services, ranging from simple leased lines to extending private LANs, are commonplace today. With the continuously growing economic difficulties, capital meltdown and telecommunication business turmoil, delivering those VPN services at the lowest cost or with the maximum revenue margin, while committing to service level agreements (SLA), has become essential. We show that whether we tackle the VPN design problem from an incumbent local exchange carrier (ILEC) standpoint or from a competitive local exchange carrier (CLEC) standpoint, we obtain contradictory rules. We show that by building edge disjoint VPN trees and splitting the traffic among them, the ILEC can achieve maximum throughput, revenue, and better network performance. On the other hand, by concentrating all the VPN traffic over a single tree, the CLEC can minimize the cost of leased bandwidth while meeting minimum SLA targets. We then propose two simple algorithms that can help carriers and service provides, respectively, leverage their networks and increase their revenue margins while committing to tight SLAs with their customers.

Link quality estimation (LQE) in wireless sensor networks (WSNs) is a fundamental building block for an efficient and cross-layer design of higher layer network protocols. Several link quality estimators have been reported in the literature; however, none has been thoroughly evaluated. There is thus a need for a comparative study of these estimators as well as the assessment of their impact on higher layer protocols. In this paper, we perform an extensive comparative simulation study of some well-known link quality estimators using TOSSIM. We first analyze the statistical properties of the link quality estimators independently of higher-layer protocols, then we investigate their impact on the Collection Tree Routing Protocol (CTP). This work is a fundamental step to understand the statistical behavior of LQE techniques, helping system designers choose the most appropriate for their network protocol architectures.

End-to-end multicast congestion control (MCC) is a complex problem. There exist two categories of multicast congestion control. The first category is single rate MCC, where the source adjusts its rate according to the slowest receiver within the session. The second category is multi-rate MCC, where the source has to disseminate the data in multiple layers and each receiver could subscribe to the required layers according to their own capacities. Among the recently proposed multicast congestion control protocols is TFMCC, which is an equation based single rate protocol. In TFMCC, at each RTT, each receiver estimates its throughput using an equation that estimates the steady-state throughput of a TCP source. The receiver with the lowest such value is declared as the current limiting receiver (CLR). The source then adjusts its rate to that of the CLR. Our objections to TFMCC are with respect to the equation adopted as well as to the slow reaction of the sender to congestion conditions. In this paper we propose two modifications to TFMCC. First, each receiver estimates its throughput using an equation that models the steady state throughput of a multicast source controlled according the additive increase multiplicative decrease (AIMD) approach. The second modification consists of monitoring RTT variations at the source side in order to rapidly adjust the sending rate to network conditions. Simulation results show that these two modifications results in remarkable performance improvement with respect to throughput, time to react, and magnitude of oscillations.

This paper describes an on-line, end-to-end and non-intrusive approach to estimate the vocal transmission quality over wireless ad-hoc networks. The proposed assessment algorithm, denoted PEVOM (Perceptual Evaluation of Voice over MANETs), is based on the fact that the observed quality of packet bas

Wireless sensor networks (WSN) are the subject of widespread deployment in commercial and military environments that call for security. Since sensor networks pose unique challenges, traditional security techniques used in traditional networks cannot be directly applied. A previous work defines TinySec, a link layer security protocol for TinyOS to provide integrity and confidentiality of messages for WSN. However, TinySec employs a simple group key management where a single shared key is stored in each sensornode. This makes the network unsecured and vulnerable to attacks. Therefore, TinySec must be enhanced with a more robust key management scheme. This paper presents the integration of a proposed key management scheme as a more robust key management solution for TinyOS. The more secured TinyOS is evaluated in terms of key computation time, memory, and energy consumption overhead. Experimental results demonstrate that the secure key management protocol introduces negligible overhead and does not affect the system performance. We also present performances comparison with two well known key distribution protocols, implemented specially for sensor networks namely, ECDLP and LEAP.

Interactive audio streaming over mobile wireless ad-hoc networks is a difficult task since these networks exhibit challenging characteristics such as mobility of all nodes, limited end-to-end bandwidth, high error rate, etc. Interactive network applications require the reception of each media unit before its deadline in order to guarantee a continuous playback process. To satisfy this constraint, a de-jitter buffer is installed on receiver host in order to mitigate the effect of delay jitter on perceptual quality. To maximize the perceived quality and to minimize the buffer space allocated by the playback audio process, the de-jitter delay must be adapted dynamically within an audio session. In this paper, we propose an adjustment playout algorithm for interactive audio applications over wireless ad-hoc networks. The proposed algorithm denoted MAP A (mobility aware playout algorithm) adjusts the playout delay based on both node mobility, which characterizes mobile ad-hoc networks, and talk-spurt, which is the intrinsic characteristic of a voice signal. The mobility detection mechanism is done at the receiver application layer. We assess the perceptual quality using an advanced evaluation method based on E-Model concepts and including the variable nature of impairment during an audio session. Simulation results show that the proposed algorithm outperforms significantly conventional playout algorithms specifically over a highly varying topology.

Transmission of digital interactive voice over ad-hoc networks is a challenging task since these networks exhibit challenging operational conditions such as mobility of all nodes, frequent session loss, random loss, energy consumption, etc. In this paper we present, EVOM, a software-based platform. EVOM (Evaluation of Voice over MANET) is designed to assess objectively the perceived quality of transmitted voice traffic over a wireless Mobile Ad-hoc NETwork (MANET). This framework uses the Real-time Transport Protocol (RTP) to build an adaptive voice application over a MANET. It also implements voice activity detection (VAD) and several playout algorithms. It provides implementation of advanced methods to assess objectively both the listening and conversational quality as perceived by real users. The used methods combine adequately the PESQ (Perceptual Evaluation of Speech Quality) algorithm and the E-Model approach and include the effect of variable nature of network state. EVOM can be used to evaluate new codecs as well as new playout algorithms and their robustness in a MANET. In addition, it can be used to develop new models representing equipment impairment of VoMANET. Moreover, it can be used to tune parameters of the algorithms involved to specific mobility scenarios and nodes density in order to achieve the best performance.

Due to the lack of built-in quality of service support, IEEE 802.11 ad-hoc networks presents serious defies in meeting the demands of multimedia applications. To overcome such challenges, research in providing QoS guarantee in ad-hoc networks has been widely studied in latest years, and several QoS approaches have been proposed. Actually, cross-layer approaches have fascinated the attentions of researchers. They have interested at particular features of network performance by developing a multitude of cross-layer optimizations and adaptations implemented into several cross-layer architectures. We think that it is time that these various personal efforts be put into perspective; and that it is time to have a cross-layer architecture model which can serve as blueprint for development of cross-layer systems. In this paper, we take a step in that direction.

Assuring effective real-time audio communication over an ad-hoc network composed of mobile wireless nodes is an important new challenge in the wireless arena. In this paper, we propose a new playback algorithm denoted PAA (Periodic Adaptive Algorithm) which adapts periodically the playback latency based on the observation of network delay. The parameters of the algorithm have been chosen off-line with traces generated from several simulated scenarios. We show that PAA outperforms both IPolicy and E-Policy algorithms with respect to Mean Opinion Scores (MOS) performance indicator.

Criticality metrics is a type of predictive models used in VLSI design. This work demonstrates that timing in physical design could be substantially improved if circuits were subjected to timing criticality analysis prior to layout and new criticality metrics were used to drive layout system. These new metrics are computed as ratios of net physical characteristics to the net delay bounds determined by an optimal bounds computation algorithm. Attempts to develop criticality metrics prior to layout were made before, but these metrics were not based on the bound ideology. The paper provides probabilistic interpretation of new criticality metrics and derivation of some important properties of these metrics. Evaluation of net criticality by new metrics can be easily merged with any layout system that allows weights to be assigned to nets on placement and/or routing steps. The methodology has been tested with a commercial layout system from a leading CAD provider. When the new criticality information was supplied to a basic commercial standard cell placer and router, timing was improved by 29.5% for the set of testcases. The achieved result is 12% better than timing generated by a targeted timing-driven layout system from the same provider. All additional computations related to the new criticality metrics require only negligible increase in run time of the basic layout system.

In this paper we employ fuzzified simulated evolution and stochastic evolution algorithms for VLSI. standard cell placement targeting low power dissipation and high performance. Due to the imprecise nature of design information at the placement stage, the various objectives and constraints are expressed in fuzzy domain. The search is made to evolve towards a vector of fuzzy goals. The proposed algorithms are compared with genetic algorithm.

The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. This choice is dictated by physical and technological constraints and must optimize several objectives. Example of objectives are monetary cost, network delay, and hop count between communicating pairs. Furthermore, due to the nondeterministic nature of network traffic and other design parameters, the objective criteria are imprecise. Fuzzy logic provides a suitable mathematical framework in such a situation. We present an approach based on the simulated evolution algorithm for the design of campus network topology. The two main phases of the algorithm, namely, evaluation and allocation, have been fuzzified. To diversify the search, we have also incorporated tabu search-based characteristics in the allocation phase of the SE algorithm. This approach is then compared with the simulated annealing algorithm, which is another well-known heuristic. Results show that on all test cases the simulated evolution algorithm exhibits more intelligent search of the solution subspace and was able to find better solutions than simulated annealing.

VLSI standard-cell placement is an NP-hard problem to which various heuristics have been applied. In this work, tabu search placement algorithm is parallelized on a network of workstations using PVM. The objective of the algorithm is to achieve the best possible solution in terms of interconnection length, overall area of the circuit, and critical path delay (circuit speed). Two parallelization strategies are integrated: functional decomposition strategy and multi-search threads strategy. In addition, domain decomposition strategy is implemented probabilistically. The performance of each strategy is observed and analyzed.

A fuzzy simulated evolution algorithm is presented for multi-objective minimization of VLSI cell placement problem. We propose a fuzzy goal-based search strategy combined with a fuzzy allocation scheme. The allocation scheme tries to minimize multiple objectives and adds controlled randomness as opposed to original deterministic allocation schemes. Experiments with benchmark tests demonstrate a noticeable improvement in solution quality.

In the pipeline banyan (PB), the reservation cycle in the control plane is made several times faster than payload transmission in data plane. This enables pipelining multiple banyans. It is observed that the ratio of throughput to switching delay (service rate) is relatively low in the PB due to the banyan. For this, we present a scalable pipelined asynchronous transfer mode (ATM) switch architecture employing a family of dilated banyan (DB) networks together with their complexity analysis and performance. A DB can be engineered between two extremes: (1) a low-cost banyan with internal and external conflicts, or (2) a high-cost conflict-free fully connected network with multiple outlets. Between the two extremes lies a family of DBs having different switching delays and throughputs. Increasing the dilation degree reduces path conflicts, which produces noticeable increase in service rate due to increase in throughput and decrease in path delay. Compared to PB, the pipelined dilated banyan (PDB) requires smaller number of data planes for the same throughput, or provides higher throughput for a given number of data planes. Simulation of PDB is carded out under uniform traffic and simulated ATM traffic. We study the switch performance while varying the load, buffer size, and number of data planes. To analyze the robustness of the switch, we show that performance is not degradable under ATM traffic with temporal and spatial burstiness generated using the on-off model. The PDB is scalable with respect to service rate and can be engineered with respect to: (1) cell loss rate; (2) hardware resources; (3) size of buffers; (4) switching delays; and (5) delay incurred to higher priority traffic. The PDB can deliver up to 3.5 times the service rate of the PB with only linear increase in hardware cost.

A new technology mapper (SELF-Map) for Look-Up Table (LUT) based Field Programmable Gate Arrays (FPGAs) is described. SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. Experimental results show that SELF-Map has an overall better performance compared to other algorithms reported in the literature.

In this paper we address the problem of optimizing mixed CMOS/BiCMOS circuits. The problem is formulated as a constrained combinatorial optimization problem and solved using an tabu search algorithm. Only gates on the critical sensitizable paths are considered for optimization. Such a strategy leads to sizable circuit speed improvement with minimum increase in the overall circuit capacitance. Compared to earlier approaches, the presented technique produces circuits with remarkable increase in speed (greater than 20%) for very small increase in overall circuit capacitance (less than 3%).

We present a novel ATM switch called parallel-tree Banyan switch fabric (PTBSF) that consists of parallel Banyans arranged in a tree topology. Packets enter at the topmost Banyan. Internal conflicts are eliminated by using a conflict free 3/spl times/4 switching element which distributes conflicting cells over different Banyans. Thus, cell loss may occur only at the lowest Banyan. Increasing the number of Banyans leads to noticeable decrease in the cell loss rate. The switch can be engineered to provide arbitrarily high throughput and low cell loss rate without the use of input buffering nor cell pre-processing. The performance of the switch is evaluated analytically under uniform traffic load and by simulation under a variety of ATM traffic loads. Compared to other proposed architectures, the switch exhibited stable and excellent performance with respect to cell loss and switching delay for all studied conditions as required by ATM traffic sources. The advantages of PTBF are modularity, regularity, self-routing, low processing over head, high throughput and robustness under a variety of ATM traffic conditions.

Mobile communication is one of the fastest growing sectors of the telecommunication industry. Mobile users can make and receive calls while they are moving independent of time, location and network access. The Global System for Mobile communication (GSM) is a pan-European digital cellular mobile system supporting widespread roaming and personal communication services (PCS) in a worldwide wireless communication network. However, wireless mobile systems are more vulnerable to fraudulent access and eavesdropping. Although the authentication process in GSM provides a reasonable security level it overloads the network with significant signaling traffic and increases the call set up time. The signaling load and the authentication delays are of particular importance and are becoming the subject of widespread research interest. We study and analyze the GSM privacy and authentication protocols, and propose a new authentication protocol with less signaling traffic and better call set up time, that can be used in GSM networks.

No abstract available.

Current placement systems attempt to optimize several objectives, namely area, connection length, and timing performance. In this paper we present a timing-driven placer for standard-cell IC design. The placement algorithm follows the genetic paradigm. Besides optimizing for area and wire length, the placer minimizes the propagation delays on a predicted set of critical paths. The paths are enumerated using a new approach based on the notion of /spl alpha/-criticality. Experiments with test circuits demonstrate delay performance improvement by up to 20%.

Novel methodology and algorithms for the derivation of timing constraints on all the interconnects were developed and applied to solving layout related timing problems. This methodology is based on detailed information on timing characteristics of cells and nets. A minimax approach for identifying maximal delay bounds for nets which do not violate the timing constraints on any of the logical paths in the design was proposed. An approximation algorithm with proven polynomial time behavior was described. The recursive application of this algorithm results in the distribution of the whole remaining path slacks between the comprising nets, and as a result, zero slack is achieved. The obtained timing bounds were applied to produce layouts free from timing problems.>

An approach is proposed to the prediction, prior to layout, of the paths and nets that will most likely be critical after layout. The approach makes use of the notion of categorization. The parameters that are highly correlated with the total path delay are first identified. These parameters are combined in a single score function. This function is evaluated for each enumerated path. The k paths with the smallest scores (or largest depending on the score function) are the most critical paths. The nets covered by the selected paths are the predicted critical nets. The nets are also ranked according to their coverage frequencies, timing (load factors), and physical characteristics (number of loading pins). A description is given of the delay model used and the authors' approach to the prediction of the dangerous paths and nets. Some experimental results are presented.>