In this paper, we propose an HSM-based architecture to detect insider attacks on server-side data. Our proposed architecture combines four cryptography-based defense mechanisms: Nonce-Based Process Authentication (NBPA), Hash-Based Field Integrity (HBFI), Hash-Based Field Availability (HBFA), and Hash-Based Row Availability (HBRA). This novel architecture is designed to detect a predefined comprehensive attack model on server-side data tailored for an HSM-based architecture. The implementation results show that the throughput decrease is mostly manageable (14% for NBPA, 30-50% for HBFI, 25% for HBFA, and 43.74% for the combination of all mechanisms), with the indication that some mechanisms are more or less appropriate depending on the situation. Moreover, the HBRA mechanism performed well regarding the attack detection time (5 minutes for a database of 1000 entries).

Vehicular network services in the smart cities generate enormous data by vehicular road users, which is a critical challenge. Network traffic leads to a negative impact on safety applications. AI techniques are a promising solution to address network traffic in VANETs with V2X data. In this paper, we propose a soft voting classification model, which consists of hybrid supervised machine learning algorithms to predict traffic in the network. We evaluate the prediction performance of five well-known machine learning models and the proposed model based on various classification evaluation metrics. The simulation results show that the proposed network traffic prediction model performs better than other considered machine learning models in terms of accuracy (0.94%), time consumption (12.25 seconds) and AUROC (0.907) that proves its stability.

Internet of Things (IoT) a paradigm that brought several new communication technologies, allowing more ubiquity and real-time applications. This innovation sped up the implementation of intelligent transportation systems in smart cities. However, the use of these technologies needs the original routing protocols. The latters must meet real-time application requirements, such as reduced transmission delay, minimal packet loss, and less power consumption. This paper comes up with a novel solution LoRaWAN-based Geographic Routing Protocol (LGRP) using a multi-criteria metric taking into account delay, packet loss, distance, and relative velocity. The hybridization of LoRaWAN with 802.11p technologies is introduced to overcome challenges of urban scenarios in our protocol achievement. We carry out the routing protocol using the Network Simulator 3 (NS-3). Then, we assess its effectiveness in comparison with the greedy perimeter stateless routing (GPSR), the Ad hoc On-Demand Distance Vector (AODV), the Cross-Layer Weighted Position-based Routing (CLWPR), and the blended OpenFlow-Optimized Link State Routing (Centralized). The simulation results show that the proposed routing protocol outmatches the comparative ones in packet delivery and end-to-end delay.

Active Authentication (AA) systems continuously authenticate users on smartphones. With high quality front-facing cameras available on recent smartphones, face-based active authentication emerges as a good candidate for AA systems. On the other hand, secure authentication of mobile users is a big concern in biometric systems. Mobile match-on-card (MMOC) technique takes advantage of SIM/eSIM card as a secure element (SE) to protect biometric templates and verify users isolated from the smartphone's environment. However, resource limitations of smart cards make MMOC authentication hard to implement. In this paper, we propose two system architectures for MMOC face-based AA systems. In Cloud-assisted MMOC architecture (CA-MMOC), we use cloud resources for model selection and training. Full MMOC architecture (F-MMOC) relies only on SIM/eSIM card's resources for enrollment and verification. A quantization scheme is proposed to make the authentication system implementable on SIM cards, plus a speed-up technique to reduce on-card execution time. Using a public mobile video dataset, we evaluate the proposed system. Our evaluation results show that the proposed MMOC authentication achieves high accuracy in real-time with a small memory footprint on SIM, and is suitable for cross-platform authentication. We also implement the CA-MMOC system on a real smartphone and evaluate the system's performance overhead in terms of power consumption, CPU and memory usage.

Increasing the number of vehicles and their communications in smart cities is a critical issue that leads to road and network traffic. Traffic prediction with high accuracy and less complexity is a challenge in Intelligent Transportation System (ITS). In Artificial Intelligence (AI), Machine learning (ML) algorithms are promising solutions to prediction problems, and Deep Learning (DL) algorithms are used for more complicated issues. In this paper, we propose a comparative analysis of the prediction performance of the most five common AI algorithms used to solve classification problems. Different evaluation metrics are employed to analyze algorithms and get the most accurate one for selecting such problems. Simulation results on the Vehicular Ad-Hoc Network (VANET) dataset revealed that Random Forest (RF) as a traditional ML algorithm performed better than other algorithms in terms of accuracy (96%) and execution time (0.73 minute) for traffic prediction.

Distributed denial of service attacks are cyber-attacks that target the availability of servers. As a result, legitimate users no longer have access to the service. This can have a negative impact on an organization, such as lack of reputation and economic losses. Therefore, it is important to design defense mechanisms against these attacks. There are systems for detecting distributed denial of service attacks in the literature, which still have various shortcomings. Some of these systems detect the presence of attack traffic without identifying the attack packets or flows. Others use static thresholds and therefore cannot adapt to changes in legitimate traffic. In this paper, we propose an online system that aims to detect flooding attacks in a short timeframe and a client–server environment. The proposed detection system consists of five modules, namely features extraction and connections construction, suspicious activity detection, attack connections detection, alert generation and threshold update. The suspicious activity detection module calculates the normalized Shannon entropy by considering the source Internet Protocol address as a random variable. Suspicious activity is detected when the computed entropy is below a threshold. The threshold calculation is based on Chebyshev’s theorem. We propose a dynamic threshold algorithm to track changes in legitimate traffic. We evaluate the proposed system through simulations and using a publicly available dataset. Compared to other similar works, the proposed detection system has a better performance in terms of detection rate, false positive rate, precision and overall accuracy.

In cloud computing, a fundamental management problem with the Infrastructure as a Service (IaaS) model lies in the efficient embedding of computational and networking resources onto distributed virtualized infrastructures owned by independent cloud providers (CPs). In such a context, this issue usually referred to as the Virtual Network Embedding (VNE) problem, adds more complexity since the entire embedding process requires two mayor phases of operation: the multicloud virtual network requests (VNRs) splitting, followed by the intracloud VNR segments mapping. This paper focuses on the splitting phase problem, by proposing a VNRs splitting strategy formalized as an Integer Linear Program (ILP) model, with the objective of improving the performance and QoS of resulting mapped VNR segments, while minimizing the resource provisioning expenditures. As the VNE is classified as an NP-hard problem, a hybrid metaheuristic approach based on the Ant Colony Optimization (ACO) combined with the Tabu Search (TS) as local search operator, is proposed in order to find good feasible solutions in reasonable time. The simulation results show the efficiency of the proposed approach, which generates, in a highly reduced computing time, solution costs very close to the exact solution, with an average cost gap ranging from 0 percent to a maximum of 3.42 percent.

We investigate the performance of a dual-hop inter-vehicular communications (IVC) system with relay selection strategy. We assume a generalized fading channel model, known as cascaded Rayleigh (also called$n$*Rayleigh), which involves the product of$n$independent Rayleigh random variables. This channel model provides a realistic description of IVC, in contrast to the conventional Rayleigh fading assumption, which is more suitable for cellular networks. Unlike existing works, which mainly consider double-Rayleigh fading channels (i.e,$n=2$); our system model considers the general cascading order$n$, for which we derive an approximate analytic solution for the outage probability under the considered scenario. Also, in this study we propose a machine learning-based power allocation scheme to improve the link reliability in IVC. The analytical and simulation results show that both selective decode-and-forward (S-DF) and amplify-and-forward (S-AF) relaying schemes have the same diversity order in the high signal-to-noise ratio regime. In addition, our results indicate that machine learning algorithms can play a central role in selecting the best relay and allocation of transmission power.

Mobile devices are becoming an essential part of many users’ lives. Users exchange sometimes very sensitive data with remote servers. This raises a security problem in terms of the confidentiality and integrity of these data, and users’ privacy. Mutual authentication protocols allow a user and a server to confirm each other’s legitimacy and share a session key to encrypt subsequent communications. Several protocols have been proposed to achieve this goal. However, these have certain weaknesses, such as impersonation, lack of anonymity, the use of additional hardware, and the synchronization problem associated with the use of timestamps. In this paper, we propose a mutual authentication protocol based on elliptic curve cryptography for mobile client – server environments, which addresses the above problems. This protocol is intended to be lightweight as it is designed for resource constrained mobile devices. Moreover, we present a formal and informal analysis of the security of the proposed protocol. This latter has security attributes, such as session key security, perfect forward secrecy, user anonymity, resistance to impersonation, replay and insider attacks. Performance evaluation shows that we outperform similar protocols. Therefore, the proposed protocol is secure, efficient and suitable for mobile environments.

In cloud computing, a fundamental management problem with the Infrastructure as a Service model lies in the efficient embedding of computing and networking resources onto distributed virtualized infrastructures. This issue, usually referred to as the Virtual Network Embedding (VNE) problem, has been well studied for a single Cloud Provider (CP). However, wide-area services delivery may require to embed heterogeneous resources over multiple CPs. This adds more complexity and scalability issues, since the Virtual Network Requests (VNRs) embedding process requires two phases of operation: the multicloud VNRs splitting, followed by the intracloud VNR segments mapping. This paper addresses the problem of VNE across multiple CPs by proposing a VNRs splitting strategy which aims at improving the performance and QoS of resulting VNR segments. An Integer Linear Program (ILP) is used to formalize the splitting phase as a maximization problem with constraints. Subsequently, in order to minimize the overall delay, a multi-objective intracloud resource mapping approach formalized as a Mixed-Integer Linear Program (MILP) is adopted. Simulations with the exact method show the efficiency of the proposed strategy based on several performance criteria. In particular, the acceptance rate and the delay are respectively improved by 15.1 and 18.5 percent, while preventing QoS violations.

Future mobile networks are rightly expected to face the prospect of limited available resources. Continuous technological advances and growing number of mobile devices highlight the importance of further improving the performance of mobile networks. User mobility poses technical problems in network management. It is essential to ensure a satisfactory level of quality of service for users. To achieve this goal, self organizing networks (SONs) are potential solutions to fulfill the requirements of users using learning algorithms. In this paper, we propose an intelligent mobility model to predict future trajectory of the mobile user in mobile networks. The proposed approach has two main parts, including mobility data preparation and user mobility prediction. Our primary focus is on providing a carefully tailored mobility data from raw mobility datasets using line simplification techniques. Next, we use the accurately prepared data for learning user mobility behaviour and predicting user future trajectory using recurrent neural networks and its variants. Simulation results show a substantial decrease in execution time from 4616s to 932s for the best case. The proposed learning approach obtains a loss value of 0.10 using a model based on long short term memory (LSTM).

Finite capacity of network resources and enormous data generated by vehicles using safety and comfort applications, have made network congestion a challenge to manage in Heterogeneous Vehicular Network (HetVNET). In this paper, we propose a reliable network congestion model based on a Multiple Linear Regression (MLR), which is a supervised machine learning algorithm to predict network congestion in HetVNET. We have evaluated the performance of our proposed network congestion prediction model using a Cross-Validation test approach. Numerical results show that the proposed linear congestion prediction model is reliable, which can explain and support variability of the response as well. Moreover, we have weighted effectiveness of each considered HetVNET parameters, in association with congestion situation in HetVNET.

Network densification with Small Cells (SCs) has emerged as a key technique to increase the 5G network capacity. However, in a densified network, fast mobile nodes will experience frequent handovers with a high signaling load, handover latency, and packet loss, due to the short cell radius. Indeed, Distributed Mobility Management (DMM) protocols aim to solve the shortcomings of centralized mobility management solutions such as poor scalability and non-optimal routing. However, when the cell residence time is short, DMM protocols might suffer from increased costs and limited performance. This paper proposes a localized mobility management protocol in 5G dense SCs, based on the locator identifier separation protocol, local mobility anchoring, and fast handovers concepts. The proposed scheme divides a local domain into several location service areas, each controlled by a local anchor. We provide the analytical models of several handover metrics, namely the average total signaling cost, the data delivery cost, the handover latency, and the packet loss. Numerical and simulation results show significant cost savings, up to 30 percent in signaling overhead, up to 53 percent of packet loss, and up to 90 percent of processing load reduction at the core of the network compared to the existing lisp mobile node protocol.

This paper focuses on the problem of workload placement in an InterCloud with the view of minimizing the carbon footprint of such a computing environment. In order to reduce the ecological impact of the data center Greenhouse Gas (GhG) emissions, this paper addresses the problem as a whole, by proposing a global mathematical formulation, based on the joint optimization of the Virtual Machine (VM) placement and their related traffics, along with a workload consolidation method and a cooling maximization technique that considers the dynamic behavior of the cooling fans. As the Virtual Machine Placement Problem (VMPP) is classified as an NP-hard problem, with the addition of the traffic embedding, the problem becomes more complex and stays NP-hard. Therefore, we propose a hybrid approach, for solving such problem and find good feasible solutions in a polynomial time. The results obtained from comparing with the exact method and other reference approaches help in assessing the efficiency of the proposed algorithm, as the carbon footprint costs are relatively close to the lower bound, with an average gap of about 3 percent, and found within a reasonable amount of time.

In this paper, we address the problem of Virtual Machine (VM) placement in an InterCloud with regard to the reduction of carbon footprint in such computing environment. In order to minimize data centers’ Greenhouse Gas (GhG) emissions, this paper proposes a mathematical formulation, where the placement approach is stated as a Mixed-Integer Nonlinear Programming (MINLP) problem which aims at minimizing the carbon footprint of the InterCloud. The proposed formulation presents an accurate carbon footprint evaluation based on joint optimization techniques, such as smart and performance-aware workload consolidation, along with cooling efficiency maximization, while considering the greenness factor of the data centers and the dynamic behavior of the equipment cooling fans. Simulations with an exact method showed that, compared with other baseline approaches, the proposed mathematical model leads to optimal configurations with minimal GhG emissions in a single cloud, as well as in an InterCloud environment, and can yield savings of up to 65 percent. The proposed model has also been compared with an approach that performs blind VM consolidation, and the obtained results showed that such model can simultaneously lead to VM configuration that yields the minimum carbon footprint while performing smart VM consolidation in order to prevent Service Level Agreement (SLA) violations.

In an urban environment, intersections are critical locations in terms of road crashes and number of killed or injured people. Vehicular ad hoc networks (VANETs) can help reduce the traffic collisions at intersections by sending warning messages to the vehicles. However, the performance of VANETs should be enhanced to guarantee delivery of the messages, particularly safety messages to the destination. Data congestion control is an efficient way to decrease packet loss and delay and increase the reliability of VANETs. In this paper, a centralized and localized data congestion control strategy is proposed to control data congestion using roadside units (RSUs) at intersections. The proposed strategy consists of three units for detecting congestion, clustering messages, and controlling data congestion. In this strategy, the channel usage level is measured to detect data congestion in the channels. The messages are gathered, filtered, and then clustered by machine learning algorithms. K-means algorithm clusters the messages based on message size, validity of messages, and type of messages. The data congestion control unit determines appropriate values of transmission range and rate, contention window size, and arbitration interframe spacing for each cluster. Finally, RSUs at the intersections send the determined communication parameters to the vehicles stopped before the red traffic lights to reduce communication collisions. Simulation results show that the proposed strategy significantly improves the delay, throughput, and packet loss ratio in comparison with other congestion control strategies using the proposed congestion control strategy.

One of the most attractive features considered by the recent LTE-A standard is the introduction of femtocells in its main architecture. Rapidly, femtocell technology has been recognized as a potential solution to offload cellular networks since its deployment is expected to grow up considerably in the near future. However, the small coverage of femtocells may lead to frequent handoffs that need permanent support of the core network. Hence, to ensure seamless handovers through such networks, local mobility management remains an important task to be addressed. In this paper, we propose an efficient X2-based local mobility scheme that allows mobile users to perform handovers with minimum signaling load compared to the mobility procedures proposed in the 3GPP LTE-A standard.

In the last few years, a large variety of wireless components are increasingly running applications that need real-time and high-bandwidth features. Hence, it is imperative for network service providers to make the best possible to ensure seamless roaming through different wireless technologies. In this context, mobility management remains an important task to be investigated to improve Quality of Service (QoS) during the handover disruption time. With the standardization of SCTP/mSCTP protocols, experiencing mobility at the transport layer becomes more attractive due to the high connectivity facilities offered at this level. In this sense, several SCTP-based mobility schemes have been proposed to provide seamless handoffs through homogeneous and heterogeneous networks. Nevertheless, the proposed solutions suffer from weaknesses such as unnecessary latency and signaling load when mobile users roam inside a same administrative domain. Additionally, the QoS relevant to the disruption time is affected quite considerably by failed Selective Acknowledgment messages (SACKs) and unnecessary chunk retransmissions due to RTO expiration. In this paper, we propose an Enhanced Hierarchical Transport layer Mobility scheme (E-HTM) that reduces handoff latency and improves throughputs observed during the handoff period. Moreover, it introduces a new mobility unit to effect more efficient handoff procedures. Simulation results show that E-HTM guarantees lower handoff latency and good throughput during handovers compared to previous mSCTP-based solutions.

Design space exploration is a delicate process whose success lays on the designers' shoulders. It is often based on a trial-and-error approach. Some basic metrics can be used to guide this process. In this paper, we explore accelerating loops from C-based specifications. We built a framework in which a design style, such as software-oriented or application-specific instruction-set processor (ASIP)-oriented design, can be specified. We also propose an exploration process that allows targeting the main aspects that limit acceleration and the actions that can be made to improve it. The process is based on new loop-oriented metrics that provide insight in key design issues. They help to determine which aspects of the design between data accesses and arithmetic logic unit (ALU)/control operations limit or allow leveraging loop acceleration opportunities. We profile some benchmarks from the signal and image processing fields, such as the Turbo Decoder and the JPEG algorithms, to illustrate how loop-oriented metrics help to point out aspects that limit or improve loop acceleration. The loop acceleration process was also used to explore design architectures that can leverage, as much as possible, the loop acceleration opportunities of the sum of absolute differences (SAD) algorithm.

Broadcast is an important building block in ad hoc networks. Its challenge is to deliver a message to all nodes in the network for a reasonable cost in terms of message load and delay. Several context-aware broadcasting protocols have been proposed in order to meet this challenge, using location or proximity information in order to fine-tune retransmission decisions. However, existing protocols often target one specific setting and can reveal to be sub-optimal when settings change. Typically, optimal parameters for dense networks will differ from optimal parameters for sparse networks. To address this issue, we propose PLAN-B an adaptive proximity-based broadcast protocol that offers the possibility to define policies in order to adapt its parameters for different network settings at runtime. Our performance evaluations show that PLAN-B outperforms existing static and adaptive protocols in terms of message load in changing and unknown densities up to a factor of 2.

As pervasive computing is becoming a reality, vehicular networking is becoming increasingly popular in the research community. The prospects of increasing safety and reducing energy expenditures lay at the heart of this surge of interest. A promising technology that allows to increase both safety and energy efficiency is automated driving, where vehicles follow each other and coordinate by message passing. It is essential to build such systems on top of solid communication building blocks, such as reliable and efficient broadcast protocols. In this paper we present BROADTRIP, a specialized broadcasting protocol for vehicles transiting in platoons. It leverages on location information and network coding in order to reduce the number of retransmissions needed to broadcast messages in platoons. We compare it with existing protocols through simulations, and show that BROADTRIP outperforms the next best comparable approach by 12% to 38% depending on settings.

This paper addresses the Multi-Layer (ML)/Multi-Region (MR) optimal path computation problem in Generalized Multiprotocol Label Switching (GMPLS) networks. Within the context of traffic engineering, path computation consists of routing Label Switched Paths (LSPs) under a multitude of constraints while optimizing resource utilization. One such problem consists of finding a shortest path in a heterogeneous GMPLS network where the different link switching types and node switching adaptation capabilities present their own set of constraints. We argue that most work have overlooked these constraints perhaps due to an ambiguous interpretation of the switching adaptation functions defined by GMPLS. To this end, we propose a novel GMPLS path computation algorithm including a binary integer program (BIP) formulation which considers the complete set of ML/MR node adaptation constraints related to nesting, un-nesting and conversion.

Applications aimed at enhancing the experience of vehicular transportation have been increasing in recent years with the widespread diffusion of smart mobile devices with network capabilities and access to user location. Such applications include navigation systems and location-based timetables. However, most of these applications only use individual contextual information in order to provide useful services to the end user. Sharing contextual information with other users can open a host of new possibilities, such as providing live traffic monitoring, where the location and the speed of individual cars are shared and indicates the flow of traffic; or friend locating, where the location of friends can be displayed on a map. In this paper, we argue that there is a lack of specialized programming support for such applications and we present DYMES, a dynamic messaging service devised to help fill this gap. Central to DYMES is a dynamic publish/subscribe system, which allows the publication of dynamic contextual information and the creation of dynamic context-based message filters. We present the core APIs provided by DYMES and illustrate their usage via two typical VANET applications. Furthermore, we identify and discuss implementation issues which guide the architectural choices in our ongoing work.

This paper proposes a mathematical model for assigning Node Bs to switches in UMTS networks, as well as an implementation of the tabu search metaheuristic for solving such a problem. In this model, the overall problem is divided into two assignment sub-problems: the assignment of a set of Node Bs to a set of radio network controllers (RNCs), and the assignment of those RNC concurrently to a set of voice switches (MSCs: Mobile Switching Centers) and a set of data switches (SGSNs: Serving GPRS Support Nodes). In order to solve the overall assignment problem, the proposed implementation defines a number of moves which enable to efficiently explore the set of possible solutions. Computational results enable to identify the parameters that are able to reduce the costs of the obtained solutions, as such costs are relatively close to the estimated lower bounds and found in reasonable computational time.

Maximizing network lifetime and minimizing energy consumption are among the central concerns in the design of applications and protocols for wireless sensor networks (WSN). Clustering has been proven energy-efficient in sensor networks since data processing, filtering routing and relaying are oper ated only by cluster heads, thus reducing network load and alleviating the bandwidth. In this paper, we propose a novel distributed clustering algorithm where cluster heads are elected following a three-way message exchange between each sensor and its neighbors. Sensor's eligibility to be elected cluster head is mainly based on its residual energy and its degree. Our protocol has a message exchange complexity of O(l) and a worst-case convergence time complexity of O(N). Simulations show that our algorithm outperforms EESH, a recently published distributed clustering algorithm, in terms of network lifetime and ratio of elected cluster heads.

The recent development and deployment of wireless technologies has created different types of mobile networks. In order to take advantage of this heterogeneity, next generation mobile networks (NGMN) is projected to integrate all of those systems. Several integrating solutions are available in the literature, yet none can claim to be the ultimate and unique integrated solution. Moreover, these proposals fail to guarantee seamless mobility and service continuity. This paper proposes a new hybrid interworking architecture (HIA) for 4G networks. HIA aims to integrate current and future wireless systems while hiding their heterogeneities. HIA guarantees seamless roaming and service continuity by supporting both IP layer and transport layer mobility. Numerical results show that HIA exhibits a net improvement of handoff latency and packet loss.

Minimizing energy dissipation and maximizing network lifetime are important issues in the design of applications and protocols for sensor networks. Energy-efficient sensor state planning consists in finding an optimal assignment of states to sensors in order to maximize network lifetime. For example, in area surveillance applications, only an optimal subset of sensors that fully covers the monitored area can be switched on while the other sensors are turned off. In this paper, we address the optimal planning of sensors' states in cluster-based sensor networks. Typically, any sensor can be turned on, turned off, or promoted cluster head, and a different power consumption level is associated with each of these states. We seek an energy-optimal topology that maximizes network lifetime while ensuring simultaneously full area coverage and sensor connectivity to cluster heads, which are constrained to form a spanning tree used as a routing topology. First, we formulate this problem as an Integer Linear Programming model that we prove NP-Complete. Then, we implement a Tabu search heuristic to tackle the exponentially increasing computation time of the exact resolution. Experimental results show that the proposed heuristic provides near-optimal network lifetime values within low computation times, which is, in practice, suitable for large-sized sensor networks.

The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and quality-of-service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner.

Soft vertical handoff (VHO) and admission control are usually considered as two independent mechanisms ensuring respectively packet-level QoS and call-level QoS for voice calls in loosely coupled 3G/WLAN networks. In this paper, we evaluate the impact of the soft VHO on the blocking performance of the optimal voice admission control in different mobility environments where the WLAN operates the Point Coordination Function (PCF). For this purpose, we propose an accurate analytical mobility model for the soft VHO region. Then, based on the proposed model, we derive and analyze the blocking and dropping probability expressions of the optimal voice admission control algorithm in the 3G network loosely coupled to the PCF-based WLAN. Results show us that a resource-efficient soft handoff (RESHO) performs significantly better than a static-threshold soft handoff (STSHO) particularly in WLAN mobility environments. In fact, the 3G new call blocking probability reduction gained by using RESHO compared to STSHO is largely increased when mobile station (MS) velocities have low mean and high variability which typically characterizes theWLAN mobility environment. Besides, results show us that RESHO reduces all blocking and dropping probabilities.We believe that the provided model and the presented results could help design efficient MS controlled soft VHO algorithms for emergent loosely coupled 3G/WLAN networks.

Since ASIPs were introduced in the HW/SW architecture design space, application partitioning has become more complex. Designers have more ways to accelerate applications: with ASIPs of various kinds or with dedicated hardware modules. In this paper, we present loop-oriented metrics that will be used during design-space exploration for the partitioning process of C-based designs. These metrics help designers determine which aspect of loop iterations, between data memory accesses and ALU/Control operations, offers more acceleration potential. We implemented a profiler-scheduler LOOPPROF that gathers the metrics. Our tool also helps determine which optimization techniques such as data reuse are suitable for the considered code segments. We demonstrate the use of our tool by exploring the acceleration possibilities of the ELA Deinterlacer, a video processing algorithm.

The Mobile Ad-Hoc Networks (MANET) are more and more important due to their increasing use. At the same time, the Trusted Computing Group (TCG) approach in using TPM based hardware root of trust is increasingly used in mobile devices providing a trustable source of knowledge about software composition of devices. In this paper, we develop a new approach to evaluate trust among peers in an Ad Hoc network, based on the reputation of their software composition.

Next-generation wireless networks present an all-IP-based architecture integrating the existing cellular networks with wireless local area networks (WLANs), wireless metropolitan area networks (WMANs), wireless ad hoc networks, wireless personal area networks (WPANs), etc. This makes mobility management an important issue for users roaming among these networks/systems. On one hand, intelligent schemes needs to be devised to benefit the IP-based technology, on the other hand, new solutions are required to take into account global roaming among various radio access technology and support of real-time multimedia applications. This paper presents a comprehensive performance analysis of fast handover for hierarchical mobile IPv6 (F-HMIPv6) using a proposed analytical model. Location update cost function, packet delivery cost function and total cost function are formulated respectively based on the fluid-flow mobility model. We investigate the impact of several wireless system factors, such as user velocity, user density, mobility domain size, session-to-mobility ratio on these costs, and present some numerical results.

Low cost WLAN networks are very likely to be loosely coupled to high cost 3G networks in order to provide the 3G subscribers with an extended WLAN capacity and the WLAN subscribers with the 3G ubiquitous coverage. Considering the high signaling latency when handing off critical voice calls between the two loosely coupled networks, soft vertical handoff (VHO) has already been introduced to ensure packet-level QoS however its resource efficiency is not evaluated yet. Therefore, in this paper we study the impact of mobility and soft VHO on the performance of the optimal voice admission control in terms of blocking probabilities. First, we propose an accurate analytical model for our system. Then we show that a resource-efficient soft handoff (RESHO) algorithm provides much better performance than a static-threshold soft handoff (STSHO) algorithm in WLAN mobility environments. In fact, we observe that the 3G new call blocking probability reduction gained by using a RESHO algorithm compared to a STSHO algorithm is largely increased when multi-mode mobile station velocities have low mean and high variability. This velocity profile typically characterizes the WLAN mobility environment. We believe that the provided model and the presented results could push and help the design of highly efficient soft VHO algorithms for loosely coupled 3G/WLAN networks.

Due to the small radio area covered by an Access Point (AP), handoffs frequently occur in Wireless Local Area Networks (WLANs) as Mobile Stations (MSs) move their associations from one AP to another. This paper presents a new handoff management scheme to support ongoing real-time applications while MSs change their network point of attachment. This approach consists of minimizing the total number of scanned channels, as well as the probe-waiting time for each examined channel. Performance is evaluated through simulations whose results show that our proposal delivers better performance, compared to the IEEE 802.11b Standard, the IEEE 802.11b Standard with Min in which an MS only waits forMinChannelTimeon each examined channel and two other well- documented solutions in the literature: Selective Scanning plus Caching and Neighbor Graphs.

Maximizing network lifetime and minimizing energy consumption and are two central issues in the design wireless sensor networks (WSN) protocols. In this paper, we address energy-efficient state assignment to sensors in cluster-based WSN, under the constraint of full coverage of the area the sensors are deployed in and connectivity of cluster heads. We consider that any sensor can be turned on, turned off or promoted cluster head, each of these states having a predefined power consumption level.We propose a sensor state assignment heuristic that processes an energy-efficient sensor configuration where every sensor is connected to a cluster head. Besides, we constraint any admissible configuration to have all its cluster heads forming a spanning tree used as a logical routing topology. First, we formulate this global problem as an Integer Linear Programming model that we prove NP-Complete. Then, we implement a greedy heuristic and we show that, compared to its lower bound, this heuristic provides quite good network lifetime values while performing low computation times, practically suitable for large-sized sensor networks.

Mobility management with provision of seamless handover is crucial for an efficient support of global roaming of mobile nodes (MNs) in next-generation wireless networks (NGWN). Mobile IPv6 (MIPv6) and its extensions were proposed by IETF for IP layer mobility management. However, performance of IPv6-based mobility management schemes is highly dependent on traffic characteristics and user mobility models. Consequently, it is important to assess this performance in-depth through those two factors. The performance of IPv6-based mobility management schemes is usually evaluated through simulations. This paper proposes an analytical framework to evaluate the performance of IPv6-based mobility management protocols. This proposal does not aim to advocate which is better but rather to study the effects of various network parameters on the performance of these protocols to enlighten decision-making. The effect of system parameters, such as subnet residence time, packet arrival rate and wireless link delay, is investigated for performance evaluation with respect to various metrics like signaling overhead cost, handoff latency and packet loss. Numerical results show that there is a trade-off between performance metrics and network parameters.

Dynamic admission control is a very important mechanism that aims, not only to check resources availability, but also to verify QoS constraints satisfaction. In this paper, we propose a new admission control mechanism in MPLS-based packet-switched networks. This admission control mechanism satisfies delay constraints for all the network connections. The admission control mechanism is based on solving a mixed linear programming model which is shown NP-hard. As real instances are relatively small sized (20 to 30 nodes), an exact resolution using the CPLEX software suite can be done. Numerical results are then given and discussed.

In this paper, we address the problem of maximizing sensor networks lifetime under area coverage constraint. For that, we propose a scheduling mechanism that calculates, for every time slot of the network operating period, an optimal covering subset of sensors that will be activated while all other sensors will go on Sleep. This mechanisms aims to balance energy dissipation over sensors, thus maximizing network lifetime. We model this problem as an Integer Linear Programming (ILP) problem, that we resolve using ILOG CPLEX and we show that the obtained solutions provide for more balanced energy consumption when we increase a balancing exponent lambda, which increases network lifetime. We finally propose a greedy heuristic that could be implemented to tackle the exponentially-increasing processing time of CPLEX.

Mobility management, with provision of seamless handoff and quality of service (QoS) guarantees, is one of the key issues in next generation or 4G wireless networks (NGWN/4G). Current trends in communication networks evolution are directed towards an all-IP principles in order to hide heterogeneities and to achieve convergence of various access networks. Several IPv6-based mobility management schemes have been proposed for service continuity in NGWN/4G. However, these schemes have some well-known disadvantages such as signaling traffic overhead, high packet loss and high handoff latency, thereby causing a user-perceptible deterioration of real-time applications. This paper proposes an efficient handoff protocol for NGWN/4G, called handoff protocol for integrated networks (HPIN), that alleviates service disruption during handoff. HPIN is a one suite protocol that performs local mobility management, fast handoff, context transfer and access network discovery. Performance evaluation based on numerical results shows that the proposed scheme performs better than existing schemes.

Achievable performance gains, when accelerating applications using ASIPs, with a good sequence of specialized instructions, depends on the applications' available parallelism, and possibilities for optimizations and transformations. The type and number of operations, and the number of data transfers of the application are also critical factors. Much progress has been done on ASIP customized instruction-identification and selection research; they are usually based on operation clustering. In this paper, we propose to minimize the number of data transfers during execution of specialized instructions sequence by storing temporary values in user-defined registers. The method avoids costly data transfers and allows parallel processing of demanding computations. This method is applied to the design of an ASIP dedicated to edge line average deinterlacing, an algorithm used in HDTV. Experimental results show that our design method applied to this application, yields a speedup factor larger than 18.

Next generation mobile networks (NGMN) are expected to integrate several heterogenous wireless technologies in order to provide high system capacity and cost effective global service coverage. In this paper we propose an efficient predictive admission control policy for heterogenous wireless bandwidth allocation. We predict well chosen traffic parameters using neural networks and we estimate blocking probabilities using generally distributed traffic models. Furthermore, we use a Tabu search algorithm to find the optimal guard band for a multi-layer heterogenous NGMN. The objective of our multi-layer predictive admission control policy (MLPAC) is to minimize global blocking probability while guaranteeing a hard constraint on handoff dropping probability. It extends the overflow scheme used in two-layer hierarchical cellular systems (HCS) to multiple heterogenous access technologies in NGMN. Presented results show that our MLPAC approach is more efficient in allocating the scarce heterogenous wireless bandwidth to a higher number of accepted connections while maintaining minimal guard bands for horizontal and vertical handoff protection.

Ad hoc wireless networks (AWNs) obey a unique organizational and behavioral logic since they operate without a fixed infrastructure. Mobile nodes must collaborate amongst themselves to interconnect, organize the topology and establish communication. Moreover, their networking characteristics highlight a new breed of unresolved routing and Quality of Service problems. This article presents new approach for QoS support in AWNs. The fundamental idea behind our approach is to identify nodes in the network that can partake in a QoS mobile routing backbone (MRB). Only nodes having routing abilities and sufficient resources can join the backbone. QoS is supported through efficient bandwidth allocation and load balancing. The routing mechanism guides incoming data flows through network regions made up of nodes rich in resources and interconnected through stable links. Results obtained are encouraging and bring to light the ability our mechanisms to support QoS in AWNs.

In this paper, we propose a local search heuristic to find "good" feasible solutions in order to solve the global planning problem of universal mobile telecommunications system (UMTS) networks. The global problem is composed of three different subproblems: the cell, the access network and the core network planning subproblems. The global model is very complex to solve exactly and for this reason, we concentrate our efforts on the development of efficient heuristics. A detailed example illustrates the solutions obtained with the proposed approach. Computational results show that our heuristic produces results that are, on average, within 5.48% of the optimal solution.

This paper proposes a new mathematical formulation to address the problem of cell assignment in UMTS network. To solve the problem, an adaptation of the tabu search metaheuristic is proposed. In this adaptation, applicable movements are well defined in order to efficiently explore the search space. Each movement has an associated gain that helps assess the degree of improvement of a current solution. Simulation results enable to evaluate the heuristic parameters that give the best solutions.

The UMTS system and architecture are designed to accommodate Internet-like mobile services and specific services like mobile commerce to mobile users. They bring attacks from Internet and mobile users as well. Denial-of-service (DoS) attacks aim to frustrate a legitimate user's access to mobile services or bring down servers by depleting system resources. Many approaches are proposed to thwart these attacks. A client puzzle from the server, which forces the client to resolve it before communication, is one of these approaches. The server can adjust the difficulty levels of the puzzle for access control and against DoS attacks according to current resource consumption and communication scenario. Currently, many types of client puzzles have no fine-grained control over difficulties. In a client puzzle, the next higher difficulty level is often twice as hard as the current one. In this paper, we propose a method based on partial collisions in hash functions. Our approach provides fine-grained control over difficulties by introducing a quasi partial collision concept. The results obtained confirm the fine granularity and efficiency of our approach.

The rapid growth in demand for location based service has encouraged research into the performance improvement for wireless sensor positioning systems. Most of proposed localization techniques for wireless sensor networks rely on multilateration or cooperative localization. In this paper, we propose a novel approach in the context of multiple-input multiple-output (MIMO) communication technique to determine the position of sensor nodes. MIMO communication systems use antenna array in both source and receive nodes to exploit the spatial properties of the multipath channel, thereby offering more information for sensor positioning. Based on estimated multipath signal parameters such as angle-of-arrival, angle-of-departure and delay-of-arrival through adaptive array signal processing techniques, the proposed approach try to minimize the errors occurring from the estimation of multipath signal parameters and gives an optimal estimation of the position of the neighbor sensor node by simultaneously resolving a set of nonlinear location equations. Computer simulations show that the position of sensor node can be determined using only one other sensor node. The mean-square errors are measured and compared with the Cramer-Rao Lower Bound to demonstrate the performance of the proposed method.

This paper proposes a resource reservation protocol to provide real-time services to mobile users. It is designed to support an integrated services network that maps the MPLS fields into IPv6's in order to simplify the protocol stack. The IPv6 Flow Label field is used to carry the MPLS label but its original value is restored at the egress node in order to keep this mechanism transparent from the user's point of view. Preliminary results show that the delays incurred to perform basic operations are low compared to an end-to-end reservation protocol. At last, limiting resource reservations to the access networks improves the scalability of the solution by reducing the number of managed states in the core routers.

Integration of heterogeneous networks constitutes the main concern of the next generation of mobile networks (4G). This integration is closely related to mobility management in the sense that a mobile user will move freely across mobile networks without connection disruption. Mobile IP based approaches suffers from drawbacks such as packet loss, high throughputs and handover latency. In this paper, we propose a new SCTP (stream control transmission protocol) mobility scheme supporting vertical handoff. The proposed scheme does not require any special infrastructure and presents less handoff latency compared to MIPv6 based approaches

Wireless sensor networks (WSNs) are composed of power-restrained nodes that limit their lifetime, since the sources of energy are often non-replaceable. In this work, we deal with the power consumption problem in one application of WSNs: objects tracking in a monitored region. Different protocols have been proposed to minimize the energy consumption in such environments. Most of them are based in prediction techniques to know in advance the locations of the object, taking advantage of this information to switch off the sensor nodes as much as possible. However, little work has been done to utilize regularity in the object's behavior to reduce energy consumption. In this paper we propose a profile-based algorithm (PBA) that aims to use the information contained in the network and in the object itself to optimize energy consumption, thus extending lifetime. Simulations show that this method outperforms prediction-based strategies for a wide range of predictability values

In this paper, we propose a tabu search heuristic to find "good" feasible solutions for the global planning problem of universal mobile telecommunications system (UMTS) networks that is composed of three subproblems: the cell, the access network and the core network planning subproblems. Since this global planning problem has been proven to be NP-hard, we concentrate our efforts on the development of an efficient heuristic. Numerical results show that quasi-optimal solutions (on average, within 0.21% of the optimal solution) can be obtained with the proposed approach

We consider a WLAN network, which consists in a set of 802.11 access points (APs) in infrastructure mode. The problem to be solved consists in assigning a channel to each AP such that the total effective throughput is maximized. The solution proposed in this paper uses a distributed algorithm to solve this problem. One software agent manages one AP and is able to communicate with its neighbors in order to optimize the global effective throughput. Simulation experiments with different topologies have given very good results, even with very dense and large networks. Furthermore, comparison with optimal solutions on small networks has shown that the performance of the algorithm described in this paper is very close to optimality. Our solution is independent from service providers and can be applied to all 802.11 WLAN networks

In heterogeneous wireless networks, mobile users are able to move from their home networks to different foreign networks while maintaining access capability to their subscribed services, which refers to global mobility. One of the key challenges in global mobility management is intersystem location management, which consists of keeping track of mobile users who roam into foreign networks. This paper presents an overview of mobility management in heterogeneous wireless networks and introduces a scheme which improves location management efficiency in terms of total signaling costs and intersystem paging delay. More specifically, cost reduction reaches about 50% when comparing the proposed architecture with conventional architectures.

As many geo-located Web services will be deployed in the future, mobile clients will be interested in locating a specific application server based on requirements such as proximity, service cost per location area, bandwidth, and server utilization rates. This paper presents a middleware system called GLWSA (Geo-Located Web Services Architecture) that aims to satisfy these requirements in addition to providing a thematic factorization of common location functions in order to locate mobile clients. The GLWSA supports a set of GLWSMs (Geo-Located Web Services Manager) distributed over the mobile network. It defines protocols to discover and inform a Supplier Application Server (SAS) to migrate the service execution (from a specific client) to the nearest SAS based on the client's location. This architecture is suitable to assist mobile clients to discover the geo-located Web services and to maintain the service execution closest to their location.

This paper defines a resource reservation protocol called hierarchical proxy mobile resource reservation protocol (HPMRSVP). This protocol is based on the hierarchical architecture HMIPv6 and used a modified version of FHMIPv6 to handle the handover. During a session, the resource reservation between two mobile nodes is limited to the access network. Furthermore, when a handover occurs, resources are uniquely reserved to the target access point before the handover is completed. The proposed protocol allows reducing delays and packet loss. In addition, management of refresh messages is moved to the access router, which holds the refresh reservation state for the duration of the session on behalf of the mobile unit. The access network thereby becomes responsible for upholding the session, which optimizes the utilization of the radio link.

This paper proposes a model for caching database data in mobile ad-hoc networks through caching the queries and their responses. The approach makes a distinction between the queries and their responses and caches them on separate mobile nodes. This method is driven by the fact that queries do not become invalid unless when the design of the database entities changes while data changes depending on the application that feeds information into the database. The architecture we use is hierarchical and employs three types of designated nodes: a query directory (QD), service manager (SM), and caching node (CN). The one or more QDs are responsible for caching the queries and are assigned and supervised by the SM that also oversees the mobility activities and the availability of nodes in the network and makes "managerial" decisions accordingly, including appointing backup nodes. With this model, any node that joins the ad hoc network will either contribute services to other nodes (willingness to become an SM, a QD, or a CN) or consume services offered by other nodes. This model attempts to coordinate the query executing and query caching mechanisms in a seamless manner while maintaining minimal communication among nodes. We present preliminary results of a model that was simulated using the NS-2 software and show the viability of the proposed approach.

One of the most challenging problems in global mobility management is location management which consists of keeping track of mobile users who leave their home network and roam into foreign networks that use different technologies and protocols. In this paper, we propose a model which improves location management efficiency in heterogeneous wireless networks. Such a model essentially consists of adding at the boundary location area between two different subsystems a specialized equipment called LR-ING (location register and Internetworking gateway) which is connected to the home location register (HLR) of both subsystems. Numerical results reveal that the proposed scheme enables to significantly reduce the signaling cost generated by the databases.

Mobile ad hoc networks are a type of mobile network that functions without any fixed infrastructure. This new mobility context is highly dynamic. One of the weaknesses of ad hoc networks is node configuration. The configuration issue in MANET consists in assigning IP addresses to mobile nodes and dealing with the dynamic behavior of the network. To complete node configuration, new solutions prove to be necessary. Several solutions have been proposed in the literature. However, these approaches have many weaknesses. This paper proposes an autoconfiguration protocol for MANET (APM), which is based on direct configuration of new nodes and on centralized control of the configuration service. The APM considers node arrivals, node departures, and network partitioning and merge. Theoretical computation and simulation results show that APM has low latency and low overhead compared to most configuration methods based on conflict detection.

Discovering with QoS the geo-located Web services is a great challenge in the client mobility context. In this paper, we propose a mechanism that collects for a particular geo-located Web service in a specific domain controlled by a geo-located discovery server GLWSM (geo-located Web services manager) the network bandwidth and the utilization factor of a supplier application server (SAS). Data collected are used in the application servers' selection and migration criterion. For a specific geo-located Web service, a GLWSM sends periodically a collect traffic request to all SAS that offer the concerned service in his domain. Then, each implicated SAS executes two processes: the network bandwidth quotation and the SAS utilization factor collection. In the network bandwidth quotation, a SAS interact with the mobile anchor point (MAP) of a GLWSM domain, to collect the network bandwidth. Meanwhile, the SAS utilization factor consists of collecting the SAS processor rate. To justify the benefits of our concept, we built a prototype that uses the NS-2 simulator and the RSVP (resource reservation protocol) protocol and we analyzed the consistency of the GLWSA system. Results prove that the proposed concept has a better responsiveness compare to a similar discovery servers with QoS.

This paper proposes to model each cell of future wireless networks as a G/G/c/c queueing system. As such a model has not been explicitly addressed in the literature, we apply maximum entropy principles to evaluate both traffic distribution and blocking probability within each cell. Analysis of numerical results enables to specify the conditions under which the system offers good quality of service in terms of blocking probability. More specifically, such an analysis reveals that coefficient of variation of call arrivals has more impact over the blocking probability than coefficient of variation of channel holding time.

Internet telephony can be defined as real-time voice or multimedia communications over packet switched networks, including the Internet. The advent of third generation, wireless telecommunications networks will make it much more popular by adding the wireless dimension. Millions of end-users will access Internet telephony services using wireless devices. These end-users will be highly mobile and will change locations very frequently. A key requirement in this environment is universal access. It stipulates that end-users have access to their advanced services from anywhere and from any terminal. Mobile agents can aid in meeting it in an efficient manner. They can carry services and follow roaming end-users. The paper presents the design, the implementation, and the evaluation of a mobile agent-based advanced service architecture for wireless Internet telephony. When a mobile agent carries services, subscription becomes a critical issue. The agent needs to be updated when the end-user subscribes or unsubscribes to services. Our architecture tackles the issue by proposing and evaluating two schemes: agent swapping and on-the-fly updating. Although, wireless Internet telephony is our prime target, the architecture is, to a large extent, independent of the underlying network and therefore applicable to Internet Telephony in general.

The virtual home environment (VHE) is a concept for service mobility. Several tool kits are under standardization for its realization. Beyond these tool kits, it is worth researching mobile agents. A few mobile agent based architectures have been proposed for VHE. In these architectures, mobile agents carry services and customized data and follow roaming end-users, by relocation or cloning. This paper focuses on how these agents and their clones are updated. It proposes two novel schemes for updating mobile service agents in VHE. The schemes rely on the agent's ability to notify a network entity of the changes made by end users to the customized data, and also on the agent's ability to update itself if requested. In the first scheme, the clones are updated remotely, whereas in the second scheme, an updating mobile agent tours all the clones to update them locally. We have derived requirements, articulated the schemes, built a prototype, and made measurements. The measurements indicate that the scheme where the network entity requests the updates directly performs better in most cases.

The next-generation (NG) wireless systems are envisioned to integrate the current communication systems into a seamless infrastructure, capable of allowing mobile users (MU) to access a wide range of high bandwidth wireless services. This integration of heterogeneous networks makes it difficult to locate MU as these MU move across networks using different access technologies and protocols. In this context, global roaming management constitutes a challenging problem. This paper presents an efficient approach which facilitates interoperability between heterogeneous networks during global roaming situations. Preliminary results reveal that such an approach significantly improves the performance of the NG wireless systems in terms of generated signaling traffic and response time during the global roaming process.

This paper presents an algorithm for minimizing the cost associated with the management of users' mobility in mobile communications networks. This algorithm allows one to determine the optimal size of a location area and to find the optimal cellular grouping model in polling regions. It guarantees the global minimum of the total cost function, while respecting the pre-established delay constraints. It takes into account the average probabilities of received calls, movements, updates and paging costs. This algorithm also allows one to avoid the problem of evaluating the cost function in a large number of points, which makes it usable on machines with limited computing power.

The "explosive growth in bursty traffic" changes the network dynamics and requires a good evaluation of various classes of service when designing an access network. From a topological standpoint, the multiservice networks in this paper are heterogeneous systems which integrate both a core and some wireless access networks into an infrastructure similar to third-generation wireless networks. Such networks require reliable and cost-effective solutions to the problem of selecting access technologies for satisfying performance and quality of service requirements related to the services and applications envisioned. This paper analyzes the reliability aspects of some access network topologies to insure a certain level of quality of service at the lowest cost for the end users. It considers a mass market equivalent to 1.6 million subscribers, the objective being to determine the cost the users are ready to pay to benefit from services and applications provided by these multiservice networks. For these purposes, the relative behavior of 3 access-network topologies are studied: the tree with parallel backup links, the ring, and the partially meshed topologies. In ring topology, simulation results show that a great connectivity in the access network is not justified in terms of reliability requirements; the partially meshed topology, even if it has redundant links which affect its cost, outperforms the tree with parallel backup links; and the ring topology is more reliable in terms of disconnected sessions than the tree topology. By considering both reliability and cost, a tree with parallel backup links appears the best topology for the access network and its cost is acceptable for the end user. This study can be extended by: (1) establishing the cost as a function of the quality of service; (2) optimizing the partially meshed topology for more reliable networks; and (3) defining a (shaping) policy to deal with a variety of traffic schemes.

The design of wireless telecommunications networks is a complex process, which requires solving simultaneously many difficult combinatorial optimization problems. We propose a taboo-search approach dedicated to one of the aforementioned design optimization problems, namely the cell assignment problem. Our approach defines a series of moves applicable to an initial solution in order to improve the cost and establish the feasibility of the solution. For this purpose, we identify a gain structure with update procedures to efficiently choose the best solution in the current neighborhood. The results are generally good in comparison with those obtained through other heuristic methods.

This paper presents a machine learning approach to the topological optimization of computer networks. Traditionally formulated as an integer program, this problem is well known to be a very difficult one, only solvable by means of heuristic methods. This paper addresses the specific problem of inferring new design rules that can reduce the cost of the network, or reduce the message delay below some acceptable threshold. More specifically, it extends a recent approach using a rule-based system in order to prevent the risk of combinatorial explosion and to reduce the search space of feasible network topologies. This extension essentially implements an efficient inductive learning algorithm leading to the refinement of existing rules and to the discovery of new rules from examples, defined as network topologies satisfying a given reliability constraint. The contribution of this paper is the integration of learning capabilities into topological optimization of computer networks. Computational results confirm the efficiency of the discovered rules.

The topological design of distributed packet switched networks consists of finding a topology that minimizes the communication costs by taking into account a certain number of constraints such as the delay and the reliability. This paper proposes a genetic algorithm (GA) for generating low-cost feasible computer network topologies subject to these constraints. The implementation of this algorithm has been subjected to extensive tests in order to measure the quality of solutions. Computational results confirm the efficiency of the GA to provide good solutions for medium-sized computer networks, in comparison with well-tried conventional methods.

As the speed and number of LANs continue to increase higher and higher demand is placed on wide area networks. To support the tremendous traffic and to avoid link congestion, such networks should utilize a robust routing strategy. This paper proposes a routing algorithm called MINDEL for assigning flows to distributed network links. With polynomial complexity this algorithm tends to minimize each packet delay by avoiding as much as possible the congested routes. Numerical results confirm the efficiency of such an algorithm, particularly for large networks, which convinces us that it could be efficiently used in high-speed networks.

This paper proposes a tabu search approach for improving communication network topologies. The problem consists of finding, for a given set of nodes and traffic requirements, a network topology that minimizes the communication cost taking into account some performance and reliability constraints. For this purpose, some moves or focal transformations called perturbations are applied to a starting topology in order to reduce the communication cost or the average packet delay. Preliminary results demonstrate the capability of such an approach to improve the communication cost as well as some performance attributes of network topologies.