The rapid growth of consumer applications such as video streaming, cloud gaming, Augmented Reality/Virtual Reality (AR/VR), and Internet of Things (IoT) deployments has intensified the demand for intelligent and adaptive congestion control in communication networks. Existing centralized congestion control solutions often struggle with scalability and responsiveness under highly dynamic traffic conditions. In this paper, we present a decentralized traffic engineering framework based on Multi-Agent Reinforcement Learning (MARL), tailored to optimize routing and traffic balancing in real time. The framework introduces two types of agents: (i) Routing Agents, which dynamically adjust link weights to steer flows across alternative paths, and (ii) Balancing Agents, which regulate traffic splitting ratios over precomputed multi-path routes. Beyond agent design, we address a key yet underexplored challenge: agent placement strategy. We compare random deployment versus traffic-aware deployment (based on node degree) and evaluate their effectiveness in mitigating congestion. Using an OMNeT++ simulation environment with realistic consumer traffic patterns on the Abilene topology (a well-known Internet2 research network), we test the framework across diverse congestion scenarios. Results show that traffic-aware placement consistently improves throughput, reduces latency and packet loss compared to both random placement and traditional Equal-Cost Multi-Path (ECMP) routing baselines. These findings highlight the potential of MARL-driven, placement-aware agents to support future consumer network- ing services requiring low-latency, high-reliability, and scalable resource management.

Modern communication networks face dynamic conditions from video streaming, Augmented Reality/Virtual Reality (AR/VR), and Internet of Things (IoT) devices. We propose a federated multi-agent reinforcement learning (F-MARL) framework that leverages adaptive multi-path routing for congestion control while preserving privacy through federated coordination. Our event-driven approach triggers Federated Learning (FL) only under congestion, with energy-aware and Shapley-based client selection for resource-constrained devices. Implemented in OMNeT++, the framework achieves 28% congestion reduction versus Open Shortest Path First (OSPF), 15% throughput improvement over Multi-Agent Congestion Control (MACC), and 42% lower overhead than non-federated Multi-Agent Reinforcement Learning (MARL). Results demonstrate privacy-preserving, adaptive intelligence for next-generation networks.

International audience

International audience

Modern communication networks like 5G and 6G are increasingly integrating Distributed Artificial Intelligence (DAI) to provide fast decision-making services like traffic management despite both the unpredictable patterns of network traffic and the intrinsic dynamism of the underlying communication network. In particular, Distributed Artificial Intelligence will enable optimal network resource usage and prevent network congestion, addressing the challenges posed by the dynamic patterns characterizing complex communication networks like 5G and 6G networks.This paper focuses on designing and assessing a new traffic management solution based on a Multi-Agent Deep Reinforcement Learning (MA-DRL). Our solution aims at adapting to network conditions including changing traffic loads, fluctuating link delays, and unpredictable packet loss scenarios, to prevent network traffic congestion, while improving throughput, latency, and loss compared to existing traffic management methods.Distributed AI, MARL, Delay optimization, packet loss optimization, traffic management, congestion control

The Internet of Things (IoT) has become an integral part of modern life, with a wide array of devices and technologies seamlessly embedded in various domains. However, IoT security—particularly in authentication—remains a critical challenge. Due to their limited resources, IoT devices require lightweight and efficient authentication mechanisms tailored to their capabilities. Additionally, the heterogeneous nature of IoT, where devices have varying security requirements, calls for flexible and adaptive solutions. Mobile IoT networks face even more complex challenges, as the threat landscape can vary across different geographical areas, necessitating real-time adaptation of security measures. Despite numerous proposed authentication schemes, existing solutions fail to address jointly IoT constraints, mobility and heterogeneity. To address this issue, we propose in this paper the AAM-mIoT solution, a robust and risk-based adaptive authentication solution specifically designed for IoT architectures. AAM-mIoT dynamically selects the optimal authentication method based on both the constraints of IoT nodes and the environment. Our solution relies on cluster-based system architecture and relies on a Software-Defined Networking (SDN) controller to monitor the network, ensuring efficient and secure authentication across the IoT system. Extensive experimental evaluations demonstrate AAM-mIoT superiority to ensure security compliance satisfaction and energy efficiency.

Dense and mobile wireless networks pose a significant challenge for Medium Access Control (MAC) protocols due to communication collision. These collisions cause network disruption, high latency, packet loss, and energy waste. To tackle this problem, researchers have used Road Side Units (RSUs) in vehicular networks to coordinate between vehicles in order to detect, avoid, and resolve collisions. However, the majority of the proposed solutions are based on vehicle localization information via a Global Positioning System (GPS) and random time-slot assignment. These solutions consume a lot of energy, produce high overhead, and are inefficient. In this paper, we propose an efficient MAC protocol called Preventive Time Slot Allocation ‘’PTA’’ for vehicular networks. Our protocol minimizes future communication collisions, message propagation delay, and energy consumption by having RSUs assign time slots to incoming vehicles based on their predicted sojourn-time. Simulation results show that our protocol is capable of reducing collisions by at least 50% and communication delay by at least 40% when compared to a major state-of-the-art MAC protocol for vehicles moving in a straight line without junctions.

The Internet of Things (IoT) is a breakthrough that enables many applications and improves our daily life. Since IoT networks deploy many devices which are generally energy or computationally-constrained, it is necessary to efficiently manage their energy to maximize network lifetime. Moreover, IoT networks may face multiple security threats that must be dealt with defense mechanisms. However, these defense mechanisms reduce network lifetime. Hence, it is necessary to design solutions that reduce the impacts of defense solutions on network lifetime. In this paper, we propose a solution based on wireless Mobile Chargers (MCs) which proactively and preventively charge devices that may need energy for the execution of security services that protect the IoT network. By using Deep Reinforcement Learning (DRL), especially Deep-Q learning, our solution determines, from the current threat level, the remaining energy of the devices, and the distance from the charger, the next device to charge. Compared to approaches that are not threat-aware, our solution improves the lifetime of a rechargeable IoT network of 16 devices by 21.59%.

The Internet of Things (IoT) has gained in popularity over the years and is used in numerous applications. IoT networks employ many constrained devices, thus, finding energy is mandatory to maximize device and network lifetime. In this paper, we investigate a scheme based on wireless Mobile Chargers (MCs) to maximize device lifetime. Instead of transmitting energy to devices to only charge them back, we design a charging scheme considering the near future needs of the devices. We provide our ongoing research on a context-aware wireless energy transfer scheme to charge the devices according to the current and probable upcoming events. Our scheme is based on two modules: a context reasoning module predicting the possible future events in the IoT network and an intelligent Wireless Mobile Charger using Deep Reinforcement Learning (DRL). Our solution aims to establish a preventive charging scheme, considering the energy status and probable future events.

Current Internet of Things (IoT) and Wireless Sensor Networks (WSNs) designs struggle to meet the excessive demand for content by an increasing number of smart objects, in terms of bandwidth and energy consumption. At the same time, the presence of devices with relatively high resources in the vicinity of the IoT devices, such as fog computing, may provide a balance between the cloud and end devices. In this paper, we propose to design and implement a distributed fog caching architecture for Content-Centric Networking (CCN). Such an architecture consists of sensor sub-networks connected to one or more fog nodes that manage the internal caching policy and the interactions with fog nodes for efficient content caching and retrieval. Through extensive simulations, we show that our strategy achieves better results compared to existing strategies in terms of energy consumption, cache hit ratio, network congestion, and user satisfaction rate.

The Internet of Things (IoT) is a network that integrates a variety of heterogeneous nodes, such as connected devices (sensors, robots, and smart phones ...), connected cars, smart homes, etc. These smart objects communicate and collaborate in distributed and dynamic environments that are facing several security challenges. Trust management is one of the most important challenges in IoT. Existing trust management solutions do not meet the new requirements of IoT such as heterogeneity, mobility, and scalability. In this article, we propose a hierarchical and scalable blockchain-based trust management protocol with mobility support in massively distributed IoT systems. In our protocol, mobile smart objects disseminate trust information on service providers to the blockchain. Thus, all the objects will have a global view on each service provider in the architecture, which speeds up the trust evaluation process. In addition, our protocol is resilient against the most known malicious attacks such asbad-mouthing,ballot-stuffing, andcooperative attacks. We confirm the efficiency of our proposal through theoretical analysis and extensive simulations. Finally, we show that it outperforms existing solutions, especially in terms of scalability, mobility support, communication, and computation costs.

We deal with the threats to user privacy in the context of wireless local networks. We focus on location privacy where an adversary tries to learn a user's past and current locations. The current Wi-Fi standard is vulnerable to location privacy and mobility profiling attacks due to the transmission of personally identifying information such as the MAC address in plain text. We provide a generic mathematical model to quantify and express the privacy and elaborate a decentralised algorithm that allows users to attain their desired levels of privacy while lowering its effect on the QoS perceived by them. We evaluate our proposal with numerical simulation and mobility traces collected from Wi-Fi users in an office environment. We show that higher privacy can be obtained with a variable effect on the throughput available to users.

Vehicular Ad Hoc networks (VANETs) is a new emerging technology that aims at connecting vehicles using wireless communication technologies. With the emergence of VANETs, new advanced applications have emerged away which aim at enhancing driving safety and traffic management. These applications exploit the huge amount of data, shared between vehicles and infrastructure, through advanced data analysis. Due to resources limitation of vehicles, this increasing volume of data is stored on powerful edge computing servers spread over the VANETs infrastructure. However, these edge servers are not fully trusted, which rise new serious security and privacy challenges regarding the shared data between vehicles. In this work, we propose a new data-sharing scheme that protects the privacy of vehicles and drivers. We base our construction on consortium blockchain, smart contracts and Zero-Knowledge Proofs (ZKP) to propose a decentralized and anonymous data-sharing scheme. In addition, we propose a fine-grained data storage scheme on the top of blockchain, based on publish-subscribe model to enhance the data management. We confirm the efficiency of our scheme through extensive simulations and experiments. The numerical results showed that our protocol achieves a reasonable efficiency while guaranteeing a high level of security.

This paper addresses the problem of communication in resource-limited broadcast/receive wireless networks. In large scale and resource-limited wireless networks, such as the Internet of Things (IoT), a massive amount of data is becoming increasingly available. Therefore, implementing protocols achieving error-free communication channels presents an important challenge. Indeed, in this new kind of network, the prevention of message conflicts and message collisions is a crucial issue. In terms of graph theory, solving this issue amounts to solve the distance-2 coloring problem on the network. This paper presents a first study on dynamic management in distance-2 coloring in resource-limited wireless networks. We propose a distributed distance-2 coloring in a dynamic network where (one) new node can join the network. Our protocol assigns to the new node a correct color without re-running the whole algorithm of time slot assigning. Our protocol is time-efficient and uses only local information with a high probability.

Nowadays, IoT low power networks have been largely adopted in various scenarios such as the factory of the future, smart agriculture, smart cities, and so forth. These networks allow the interconnection of resource-constrained devices (e.g. actuators and sensors) using wireless communication links. In such networks, having energy-efficient routing protocols is necessary in order to maximize the network lifetime. However, many factors may influence the energy consumption in IoT low power networks. These factors include the transmission power of devices, the data routing strategy, etc. In this paper, we address the effect of the transmission power on energy consumption in RPL networks (RPL : IPV6 Routing Protocol for Low-Power and Lossy Networks) and propose a new solution based on a multi-layer perceptron (MLP) model, to estimate the optimal transmission range of dynamic IoT low power networks deployed following a 3D topology. The results of our experiments show that our MLP model perfoms well compared to other machine learning models.

The Internet of Things (IoT) is an emerging technology that aims to extend connectivity to all everyday devices. One of the main challenges that are slowing down its development is how to secure the Device-to-Device communication. Among all the security issues, the Key Management (KM) is one of the most challenging. The difficulty lies in the fact that most of the IoT devices suffer from a lack of resources. Although different protocols were proposed, most of them do not consider the dynamic nature of the IoT. Other solutions rely on a centralized entity to distribute the new keys upon a change in the network. However, this entity becomes a single point of failure and the main target of attacks. We propose a novel blockchain-based decentralized KM protocol. In addition to being resilient, scalable and dynamic, our solution uses the blockchain technology to securely distribute the KM on several entities.

The challenging problem of energy efficiency in security of the Internet of Things (IoT) is tackled in this article. The authors consider the upcoming generation of mobile networks, 5G, as a communication architecture for the IoT. The concept of adaptive security is adopted, which is based on adjusting the security level as per the changing context. It has the potential of reducing energy consumption by adapting security rather than always considering the worst case, which is energy consuming. The consideration of 5G introduces new dynamics that can be exploited to perform more adaptation. The proposed solution introduces an intelligence in the application of security, from the establishment phase to the use phase (end-to-end). The security level related to the used cryptographic algorithm/key is adapted for each node during the establishment phase, so to match with the duration of the provided services. A new strategy is formulated that considers both IoT and 5G characteristics. In addition, a solution based on the framework of the coalitional game is proposed in order to associate the deployed objects with the optimized security levels. Moreover, the application of security is also adapted during the use phase according to the threat level. Trust management is used to evaluate the threat level among the network nodes, while existing works focus on performing the adaptation during the use phase. The proposed approach achieves more adaptation through the consideration of both IoT and 5G dynamics. The analysis and performance evaluations are conducted to show the effectiveness of the proposed end-to-end approach.

Named Data Networking (NDN) represents a new communication paradigm, which shifts the Internet towards name-based routing. NDN relies on caching functionalities and local data storage, such as a content request could be satisfied by any node holding a copy of the content in its storage. Network coding, when combined with NDN, allows a data transfer session to use multiple sources for the content seamlessly to improve content delivery efficiency. In this paper, we address the data pollution issue which is inherent to network coding and we propose a single-path authenticated network coding mechanism for Named Data Networking, where a single route between the source to the destination is established. Packets are encoded, cached and signed among this path. First, we formulate our single-path-based optimal coding and homomorphic signature scheme as a mixed integer program (MIP) problem. We consider an optimistic model in which we focus mainly on maximizing defence level of the network. Furthermore, we show how to leverage Software Defined Networking to provide seamless implementation. Finally, we evaluate the efficiency of the proposed coding mechanism, which achieves better performance than conventional NDN with random coding especially in terms of transmission cost, processing overhead and security.

Fog computing is a new paradigm which extends cloud-computing services into the edge of the network. However, this new architecture creates new challenges in relation with data security and privacy. In fact, due to the emergence of data externalization technologies, as Fog computing, privacy has become a major concern for all users. There have been several proposals in the literature that treated privacy issues using existing anonymization techniques, but few of them considered accountability service. Whereas, when security systems do not adopt accountability mechanisms, full anonymity may encourage users to act maliciously. In this paper, we propose a novel accountable privacy preserving solution for public information sharing in fog computing architecture. Based on signatures, our scheme allows fog servers to authenticate any user in the system without violating its privacy. In case of users' misbehavior, our architecture considers an authority that is able to trace any user in the system. Our solution ensures privacy preserving and accountability services in a completely distributed manner, without resorting permanently to the authority. Finally, we show through experimentation that our solution outperforms existing solutions.

The Internet of Things (IoT) is a network made up of a large number of devices which are able to automatically communicate in a Peer-to-Peer manner. The aim is to provide various services for the benefit of society. One of the main challenges facing the IoT is how to secure this Device-to-Device communication. Among all the security issues, the Key Management is one of the most difficult. This is mainly due to the fact that most of these devices have limited resources in terms of storage, calculation, communication and energy. Although different approaches have been proposed to deal with this problem, each of them presents its own limitations and weaknesses. In this paper, we propose a novel Key Management protocol for Device-to-Device communication in the Internet of Things. Compared to the existing Peer-to- Peer schemes, our solution provides the best compromise between the IoT requirements: resilience, connectivity, efficiency, scalability and flexibility. To achieve this balance, the network members are uniformly distributed into logical sets. A device shares then a distinct pairwise key with each member of its set and a unique pairwise set key with the members of each of the other sets. We then prove that our solution is resilient as the capture of a member compromises a negligible part of a large network. Moreover, we show that our scheme has a good network connectivity. It is then efficient as it does not require additional calculation or communication costs on the network members. We also demonstrate that our protocol is scalable as storage cost on the network members does not significantly increase when the network gets larger. We finally show that our solution is flexible.

The Internet of Things (IoT) is a network made up of a large number of devices which are able to automatically communicate to computer systems, people and each other providing various services for the benefit of society. These devices have the particularity of being heterogeneous and so have different capabilities in terms of storage, computing, communication and energy. One of the main challenges facing the IoT is how to secure communication between these heterogeneous devices. Among all the issues, the Group Key Management is one of the most difficult. Although different approaches have been proposed to solve it, very few of them consider the heterogeneous nature of the IoT. We propose then a highly scalable Multi-Group Key Management protocol for IoT that ensures the forward and backward secrecy, efficiently recovers from collusion attacks, guarantees the secure coexistence of several services in a single network and balances the loads between its heterogeneous devices according to their capabilities. The evaluation of our solution shows that it is efficient for large-scale heterogeneous networks even if they contain highly resource-constrained devices.

Named Data Networking (or NDN) represents a potential new approach to the current host based Internet architecture which prioritize content over the communication between end nodes. NDN relies on caching functionalities and local data storage, such as a content request could be satisfied by any node holding a copy of the content in its storage. Due to the fact that users in the same network domain can share their cached content with each other and in order to reduce the transmission cost for obtaining the desired content, a cooperative network coding mechanism is proposed in this paper. We first formulate our optimal coding and homomorphic signature scheme as a MIP problem and we show how to leverage Software Defined Networking to provide seamless implementation of the proposed solution. Evaluation results demonstrate the efficiency of the proposed coding scheme which achieves better performance than conventional NDN with random coding especially in terms of transmission cost and security.

Nowadays, multimedia is omnipresent in the Internet and generates the major total traffic in fixed and mobile networks. While video streaming services become more crucial for mobile users, their traffic may often exceed the bandwidth capacity of cellular networks. Content Centric Networking (CCN) can be an attractive solution which adapts the network architecture to the current network usage pattern. In this paper, we propose a CCN peer-to-peer video-on-demand streaming protocol based on scalable video coding. We implement a collaborative strategy which improves the video segments availability in the network and reduces latency relying on CCN functionalities such as caching and routing by name. We also propose a control strategy allowing to scale to highly dynamic networks. Through the tests carried out to evaluate the performance of our solution, we show its effectiveness. Indeed, it reduces significantly the initial playback delay and enhances the streaming quality compared to a traditional service with no collaboration policy.

In wireless networks based on the IEEE 802.11 standard, mobile stations communicate with access points through the exchange of packets transmitted over the air. These packets can be captured by any listener in the vicinity which can extract the MAC address of the transmitter and thus be able to record the movements of the transmitter over time even when the system uses encryption as layer 2 headers, particularly the MAC address which uniquely identifies a mobile station is not encrypted. Existing solutions to this privacy breach aim at using pseudonyms to avoid using the same MAC address and also introduce silent periods to make it difficult for an attacker to track users. The introduction of silent periods may have negative effects on some applications particularly for those with constraints on bandwidth and delay such as video streaming. In this paper, we propose an enhanced silent period-based solution that allows to maximize the perceived QoS for a preset privacy. Our solution is elaborated from our mathematical model that allows to: (i) quantify the desired user location privacy and QoS, (ii) compute the silent and active periods that cope with these two objectives, and (iii) offer users the best trade-off between privacy and QoS. We experimented our proposal with a set of numerical simulations. The obtained results demonstrated the efficiency of the proposed solution.

This work considers the problem of communication in dense and large scale wireless networks composed of resourcelimited nodes. In this kind of networks, a massive amount of data is becoming increasingly available, and consequently implementing protocols achieving error-free communication channels constitutes an important challenge. Indeed, in this kind of networks, the prevention of message conflicts and message collisions is a crucial issue. In terms of graph theory, solving this issue amounts to solve the distance-2 coloring problem in an arbitrary graph. The paper presents a distributed algorithm providing the processes with such a coloring. This algorithm is itself collision-free and conflict-free. It is particularly suited to wireless networks composed of nodes with communication or local memory constraints.

Nowadays Cloud computing services are becoming a necessity due to the huge evolution of internet technology and the need of outsourcing data into external servers. However, data externalization introduces several issues. Access control is one of the most challenging issues, it must ensure data confidentiality through enforced and flexible access policies. Revocation is one of the important tasks of access control process, generally, it consists on banishing some roles from users on the system. Ciphertext-policy attribute-based encryption is a promising cryptographic method. It provides fine-grained access which makes it very useful in case of group-sharing applications. However, the challenge of this method is the revocation. Through few past years, there have been many proposed revocation solutions on ABE, but these solutions still lack of efficiency. In this paper, we propose an access control mechanism with an immediate and efficient attributes or users revocation. Our solution uses CP-ABE for a flexible and fine grained access while it provides collusion resistance, supports scalability and does not require neither rekeying mechanisms nor keys redistribution.

The proliferation of network technologies drives many different network architectures to provide huge variety of services and contents to end clients. This task becomes more difficult when we are in networks with intermittent connections, called delay tolerant networks (DTN) where security is an important issue. In this paper, we propose a trust-based approach to secure data transfer in DTN in the presence of malicious transporters. Our proposal is intended to a DTN architecture which includes several sub-networks geographically dispersed in isolated regions and having an intermittent access to an infrastructure-based network (like internet). Our approach is based on a particular web-of-trust, which is formed based on existing social relationship among clients and transporters. We conducted intensive simulations and the obtained results show that it offers high packet delivery rate and resists against malicious transporter's behaviour.

Providing efficient security services in dynamic low-power environments as the Internet of Things (IoT) is a challenging task. The deployment of static security services will consume the energy even if it is not required in some situations, so this induces a waste of resources. In this paper, we introduce an efficient model for adaptive security in the IoT based on trust management. Most of existing adaptive security approaches lack of practical means to evaluate threats. On the other hand, trust management systems are designed to deal with selfish behaviors or internal attacks and not to assist cryptographic measures. Our solution evaluates the trust level related to the presence of security threats among nodes, and adapt consequently cryptographic measures. The obtained simulation results show that our solution reduces considerably energy consumption and remains yet secure.

Wireless sensor network (WSN) is often deployed in hostile environments, which make it vulnerable to attacks. WSN comprises a large number of sensor nodes with different hardware abilities and functions. Due to the limited memory resources and energy constraints, complex security algorithms cannot be used in WSN. Hence, it is necessary to balance between security requirements and energy consumption. In this paper, we propose a lightweight public-key-based authentication protocol for WSNs. Our protocol uses identity-based encryption in order to lighten the energy consumption from the public-key certificate management. We have developed two variations of the proposed solution depending on the manner and when an attack should be detected. We perform an overall evaluation of our approach through simulations. The results indicate out performance of our approach in terms of energy consumption while providing effective security.

Optimizing energy consumption and end-to-end (e2e) packet delay in energy-constrained, delay-sensitive wireless sensor networks is a conflicting multiobjective optimization problem. We investigate the problem from a game theory perspective, where the two optimization objectives are considered as game players. The cost model of each player is mapped through a generalized optimization framework onto protocol-specific MAC parameters. From the optimization framework, a game is first defined by the Nash bargaining solution (NBS) to assure energy consumption and e2e delay balancing. Secondy, the Kalai-Smorodinsky bargaining solution (KSBS) is used to find an equal proportion of gain between players. Both methods offer a bargaining solution to the duty-cycle MAC protocol under different axioms. As a result, given the two performance requirements (i.e., the maximum latency tolerated by the application and the initial energy budget of nodes), the proposed framework allows to set tunable system parameters to reach a fair equilibrium point that dually minimizes the system latency and energy consumption. For illustration, this formulation is applied to six state-of-the-art wireless sensor network (WSN) MAC protocols: B-MAC, X-MAC, RI-MAC, SMAC, DMAC, and LMAC. The article shows the effectiveness and scalability of such a framework in optimizing protocol parameters that achieve a fair energy-delay performance trade-off under the application requirements.

In this paper, we introduce Adaptive Data-Communication Trust Mechanism for clustered wireless sensor networks (ADCT) to effectively deal with compromise or malicious nodes. Unlike prior works, we propose an adaptive function to evaluate the direct trust between nodes according to the need of the application in terms of trust severity. We also consider data trust to cope with untrustworthy nodes during the data collection despite their communication capabilities. Finally, we introduce a new method to discard a malicious recommendation when building feedback at the base station or cluster-head level. Theoretical analysis shows that our trust mechanism allows a good trade-off between memory requirement and trust cooperation.

The quality of radio communication links decreases with high temperatures. In this paper, we investigate the effect of temperature on percolation-based connectivity in large scale wireless sensor networks and show that more energy can be saved by allowing some nodes to go to deep sleep mode when temperature decreases and links improve. We determine a closed-form formula for a threshold network density equation in function of temperature τ. Beyond λ*(τ), the network percolates and guarantees connectivity. Based on this result, we propose a simple yet efficient Temperature-Aware MAC plugin (TA-MAC) that enables the underlying MAC protocol to dynamically adapt the network effective density to allow further energy savings while maintaining network connectivity. TA-MAC can be potentially used with any wireless MAC protocol. We carried out simulations and demonstrated that BMAC and SCP-MAC augmented with TA-MAC plugin allow a significant energy efficiency improvement.

Temperature variations have a significant effect on low power wireless sensor networks as wireless communication links drastically deteriorate when temperature increases. A reliable deployment should take temperature into account to avoid network connectivity problems resulting from poor wireless links when temperature increases. A good deployment needs also to adapt its operation and save resources when temperature decreases and wireless links improve. Taking into account the probabilistic nature of the wireless communication channel, we develop a mathematical model that provides the most energy efficient deployment in function of temperature without compromising the correct operation of the network by preserving both connectivity and coverage. We use our model to design three temperature-aware algorithms that seek to save energy (i) by putting some nodes in hibernate mode as in the Stop-Operate (SO) algorithm, or (ii) by using transmission power control as in Power-Control (PC), or (iii) by doing both techniques as in Stop-Operate Power-Control (SOPC). All proposed algorithms are fully distributed and solely rely on temperature readings without any information exchange between neighbors, which makes them low overhead and robust. Our results identify the optimal operation of each algorithm and show that a significant amount of energy can be saved by taking temperature into account.

This paper addresses the Internet of Things (IoT) paradigm, which is gaining substantial ground in modern wireless telecommunications. The IoT describes a vision where heterogeneous objects like computers, sensors, Radio-Frequency IDentification (RFID) tags or mobile phones are able to communicate and cooperate efficiently to achieve common goals thanks to a common IP addressing scheme. This paper focuses on the reliability of emergency applications under IoT technology. These applications' success is contingent upon the delivery of high-priority events from many scattered objects to one or more objects without packet loss. Thus, the network has to be self-adaptive and resilient to errors by providing efficient mechanisms for information distribution especially in the multi-hop scenario. As future perspective, we propose a lightweight and energy-efficient joint mechanism, called AJIA (Adaptive Joint protocol based on Implicit ACK), for packet loss recovery and route quality evaluation in the IoT. In this protocol, we use the overhearing feature, characterizing the wireless channels, as an implicit ACK mechanism. In addition, the protocol allows for an adaptive selection of the routing path based on the link quality. .

In this paper we want to explore a new approach for security mechanisms design and deployment in the context of Internet of Things (IoT). We claim that the usual approach to security issues, typical of more classical systems and networks, does not grab all the aspects related to this new paradigm of communication, sharing and actuation. In fact, the IoT paradigm involves new features, mechanisms and dangers that cannot be completely taken into consideration through the classical formulation of security problems. The IoT calls for a new paradigm of security, which will have to consider the security problem from a holistic perspective including the new actors and their interactions. In this paper, we propose a systemic approach to security in IoT and explore the role of each actor and its interactions with the other main actors of the proposed scheme.

Recent advancements in wireless charging technology offer promising alternative to address the challenging problem of energy consumption in low-power networks, as WSN for example. Based on these breakthroughs, existing solutions have investigated wireless charging strategies of low-power networks through the use of mobile chargers, where a charger has to come at the nodes' vicinity to recharge their battery. However, none of these works have considered the multihop energy transmission, whose feasibility have been demonstrated recently. In such a system, a node can transmit energy wirelessly to its neighbors. In this paper, we propose an optimization model to determine the minimum number of chargers needed to recharge the elements of a network in a multihop scenario, taking into account the energy demand of the nodes, the energy loss that occurs during a transfer and the capacity of the chargers. To the best of our knowledge, the work presented in this paper is the first that addresses the optimization of multihop wireless energy transfer in low-power networks.

Given the sensitivity of the potential WSN applications and because of resource limitations, key management emerges as a challenging issue for WSNs. One of the main concerns when designing a key management scheme is the network scalability. Indeed, the protocol should support a large number of nodes to enable a large scale deployment of the network. In this paper, we propose a new scalable key management scheme for WSNs which provides a good secure connectivity coverage. For this purpose, we make use of the unital design theory. We show that the basic mapping from unitals to key pre-distribution allows us to achieve high network scalability. Nonetheless, this naive mapping does not guarantee a high key sharing probability. Therefore, we propose an enhanced unital-based key pre-distribution scheme providing high network scalability and good key sharing probability approximately lower bounded by 1-e-1≈ 0.632. We conduct approximate analysis and simulations and compare our solution to those of existing methods for different criteria such as storage overhead, network scalability, network connectivity, average secure path length and network resiliency. Our results show that the proposed approach enhances the network scalability while providing high secure connectivity coverage and overall improved performance. Moreover, for an equal network size, our solution reduces significantly the storage overhead compared to those of existing solutions.

Given the sensitivity of the potential WSN applications, security emerges as a challenging issue in these networks. Because of the resource limitations, symmetric key establishment is one favorite paradigm for securing WSN. One of the main concerns when designing a key management scheme for WSN is the network scalability. Indeed, the protocol should support a large number of nodes to enable a large scale deployment of the network. In this paper, we propose a new highly scalable key establishment scheme for WSN. For that purpose, we make use, for the first time, of the unital design theory. We show that the basic mapping from unitals to pairwise key establishment allows to achieve an extremely high network scalability while degrading the key sharing probability. Then, we propose a new unital-based key pre-distribution approach which provides high network scalability and good key sharing probability. We conduct analytical analysis to compare our solutions to existing ones, the obtained results show that our approach enhances the network scalability while providing good overall performances. Also, we show that our solutions reduce significantly the storage overhead at equal network size compared to existing solutions.

There has been a host of research works on wireless sensor networks for medical applications. However, the major shortcoming of these efforts is a lack of consideration of data management. Indeed, the huge amount of high sensitive data generated and collected by medical sensor networks introduces several challenges that existing architectures cannot solve. These challenges include scalability, availability and security. In this paper, we propose an innovative architecture for collecting and accessing large amount of data generated by medical sensor networks. Our architecture resolves all the aforementioned challenges and makes easy information sharing between healthcare professionals. Furthermore, we propose an effective and flexible security mechanism that guarantees confidentiality, integrity as well as fine grained access control to outsourced medical data. This mechanism combines several cryptographic schemes to achieve high flexibility and performance.

Tree topologies are widely used in WSN in order to route convergecast traffic to the sink. We consider in this paper the Shortest Path routing Tree (SPT) problem in WSN under different metrics; we show that the basic SPT based strategies are unsuitable for the many-to-one WSN when considering some metrics to compute link costs. Indeed, existing SPT approaches aim to construct a tree rooted at the sink such that the cost of the path from any node to the sink is minimal, while the cost of a given path is computed as summation of the costs of links that compose this path. However, in many-to-one WSN, links which are close to the sink are more critical than other links when using some metrics. We propose in this paper a new weighted path cost function, and we show that our cost function is more suitable for WSN. Based on this cost function, we propose a simple and efficient weighted shortest path tree construction which does not introduce new overheads. We consider, then, the particular case of energy-aware routing in WSN when we apply our new solution in order to construct more suitable energy-aware SPT. We conduct extensive simulations which show that our approach allows to enhance the network lifetime up to 17% compared to the basic one.

This paper considers slotted duty-cycled medium access control (MAC) protocols, where sensor nodes periodically and synchronously alternate their operations between active and sleep modes to save energy. Communications can occur only when nodes are in active mode. The synchronous feature makes these protocols more appropriate for delay-sensitive applications than asynchronous protocols. With asynchronous protocols, additional delay is needed for the sender to meet the receiver's active period. This is eliminated with synchronous approaches, where nodes sleep and wake up all together. Moreover, the contention-based feature makes the protocols - considered in this paper - conceptually distributed and more dynamic compared to TDMA protocols. Duty cycling allows obtaining significant energy saving vs. full duty cycle (sleepless) protocols. However, it may result in significant latency. Forwarding a packet over multiple hops often requires multiple operational cycles (sleep latency), i.e. nodes have to wait for the next cycle to forward data at each hop. Timeliness issues of slotted contention-based MAC protocols are dealt with in this paper, where a comprehensive review and taxonomy is provided. The main contribution is to study and classify the protocols from the delay-efficiency perspective.

New emerging applications for wireless sensor networks as mission-critical and multimedia applications often have heterogeneous sensing capabilities and require that the network supports different types of QoS-constrained traffic at variable rates. Designing an efficient Medium Access Control protocol allowing these applications to work properly while coping with the limited resources of sensor networks is a challenging task. In this paper, we present AMPH, a new adaptive MAC protocol with QoS support for heterogeneous wireless sensor networks. AMPH provides high channel utilization with a hybrid and adpative behavior and integrates a new efficient prioritization scheme to provide QoS support and fair data delivery of heterogeneous traffic. The simulation results show the effectiveness of AMPH.

Wireless body sensors combined with ubiquitous Wireless Sensor Networks enable pervasive healthcare applications. This technology can significantly improve the quality of life of chronically ill and elderly. Remote medical monitoring applications consist of many features as continuous medical monitoring, emergency alerts, location tracking and home automation. These heterogeneous systems have to implement Quality of Service mechanisms to ensure that the different functions have their QoS requirements satisfied, that the most important traffic still has its QoS requirements fulfilled in case of network overload and finally that QoS mechanisms are able to adapt dynamically depending on the context. From our knowledge, QoS provisioning in wireless sensor networks for healthcare has never been studied from the context-awareness specific perspective, although context-awareness is the core issue of WSN for healthcare and that these networks have specific characteristics in comparison with most WSN. Health monitoring applications demand high reliability as life of human beings is involved, therefore Quality of Service support in such systems is vital. As patient may evolve from a non-critical health status to a critical one, context-awareness is essential to adapt the network performance to the new situation. In this paper we study the specific QoS requirements of healthcare applications. Then, we discuss the strengths and weaknesses of related work regarding these characteristics and context-awareness. Finally, we point out remaining challenges and open research issues.

Wireless sensor networks for rehabilitation is becoming a topic of great interest in medical applications generating a large amount of work in biomedical and communication research communities. In this line, several solutions have been proposed to provide unobtrusive, flexible and low cost systems for the supervision of rehabilitation. These solutions have focused on sensor/hardware design, platform/architecture design and signal processing algorithms. However, a little attention has been paid to network communications where there exist challenging problems specific to rehabilitation applications. In this paper, we present the design and the implementation of a new light-weight and easy to use wireless sensor network for high-fidelity rehabilitation supervision. Namely, we propose a fault-tolerant, energy-efficient communication protocol that meets the clinical requirements of rehabilitation supervision in terms of data quality and data rate. Also, we outline the implementation of this protocol on the top of the IEEE 802.15.4 standard and evaluate its performance through intensive real-world experiments and simulations.

Wireless sensor networks are becoming a topic of great interest in medical applications generating a large amount of work in medical and computer research communities. In this line, several solutions have been proposed to provide unobtrusive, flexible and low cost systems for patient supervision. However, existing solutions can not be used in rehabilitation supervision because of the specific characteristics of this application. Indeed, new major challenges arise from the fact that each sensor node needs to continuously stream large volumes of data at a high rate to enable doctors to extract clinically relevant information. In addition, the placement of several adjacent sensor nodes on the body may cause serious interferences problems. In this work, we describe and demonstrate our wireless sensor network prototype for high-fidelity rehabilitation supervision. Our demonstration allows attendees to experience the potential of wireless sensor networks for enabling flexible and low cost rehabilitation monitoring systems. In order to alleviate transmission problems, we develop a novel communication protocol that meets the clinical requirements of rehabilitation supervision in terms of data quality and data rate.

We propose, in this paper, a novel class of probabilistic key pre-distribution schemes highly resilient against node capture. We introduce a new approach to enhance resilience by concealing keys through the use of a simple hash chaining mechanism. We provide analytical analysis which shows that our solution enhances the network resilience against node capture without introducing a new overhead comparatively to similar solutions in the literature.

Lately, Peer-to-Peer (p2p) networks like BitTorrent, Limeware and eMule have gained a large popularity as free of charge services to download any kind of files, mostly multimedia contents. Recent reports indicate that near 60 percent of all the current P2P Internet traffic is due to BitTorrent. The music and movies industry, blame BitTorrent among other systems for their falling sales in the USA and Europe, and hence with the help of ISPs started to find ways to throttle their communication. BitTorrent users always found ways to override these obstacles. This ongoing cat and mouse game between ISPs and BitTorrent client developers is about to enter new level. In this paper, we analyze a proposal of a BitTorrent traffic blocking on the network layer and its effects on the peers download efficiency. Our analyses show that in worst case scenarios, our predicted throttling technique could reduce the number of peers succeeding in downloading the copyright protected content to 49 percent.

In Ad-Hoc networks, user nodes, in addition to handling their own traffic, also act as routers and contribute to network connectivity for the benefit of other nodes. With such a collaborative routing technique, hybrid Ad-Hoc networks i.e. Ad-Hoc networks interconnected to an infrastructure-based network via an Access Point (AP) - become a means to extend the network coverage of APs. However, nodes may not be continuously available to route the traffic of other nodes. This can result in severe bandwidth degradation if nodes (partially) drop data packets. In this paper, we propose a new routing protocol suite called MOOR which enables Ad-Hoc nodes to discover dynamically the most reliable routes toward the AP. It is based on a reputation cross-layer system which runs on the AP side and makes use of the TCP control mechanisms to evaluate node cooperation.

Key management is a corner stone service for any security solution for WSNs. Resources limitation of WSNs makes the public key based solutions, which offer more efficient key management services, unsuitable for wireless sensor networks. In this paper, we propose a novel efficient tree-based probabilistic key management scheme which is highly resilient against node capture attacks. Our solution is based on symmetric cryptography with a probabilistic key pre-distribution. We introduce a new approach to enhance resilience by concealing keys through the use of a simple hash function mechanism. We further improve resiliency by using the number of shared keys as criteria to construct the secure tree. We provide analytical analysis and extensive simulations which show that our solution enhances the network resilience against node capture without introducing any overhead comparatively to similar solutions in the literature.

Key management, which is an important building bloc in securing group communications, has received a particular attention in both academic and industry research communities. This is due to the economical relevance of group-based applications. The key management concerns the distribution and updates of the key material each time a member joins or leaves the group. The dynamic aspect of group applications due to free membership joins and leaves in addition to members' mobility makes difficult the design of efficient and scalable key management protocols. In this paper, we propose a new key management protocol to secure group communications where we consider the mobility of nodes in a mobile environment with a null rekeying cost. Protocol simulations show that our protocol achieves better performance in terms of rekeying.

Peer-to-peer (p2p) networking technology has gained popularity as an efficient mechanism for users to obtain free services without the need for centralized servers. Protecting these networks from intruders and attackers is a real challenge. One of the constant threats on P2P networks is the propagation of active worms. In 2007, Worms have caused damages worth the amount of 8,391,800 USD in the United States alone. Nowadays, BitTorrent is becoming more and more popular, mainly due to its fair load distribution mechanism. Unfortunately, BitTorrent is particularly vulnerable to active worms. In this paper, we propose a novel worm detection system in BitTorrent and evaluate it. We show that our solution can detect various worm scans before 1% of the vulnerable hosts are infected in worst case scenarios. Our solution, the BitTorrent worm sensor network, is built over a network of immunized agents, which their main job is to efficiently stop worm spread in BitTorrent.

Application level multicast protocols construct an overlay tree between end-hosts participating in the multicast session. The efficiently of the constructed overlay tree depends entirely on the honesty and on the cooperation of all participating members. However such behavior can not be guaranteed and some selfish and non-cooperative nodes may take profit from the honesty of other members in the overlay. In this paper we investigate the negative impact of cheating nodes on the performances and on the stability of overlay tree constructed by our MDA-ALM protocol.

Ensuring security in embedded systems translates into several design challenges, imposed by the unique features of these systems. These features make the integration of conventional security mechanisms impractical, and require a better understanding of the whole security problem. This paper provides a unified view on security in embedded systems, by introducing first the implied design and architectural challenges. It then surveys and discusses the currently proposed security solutions that address these challenges, drawing from both current practices and emerging research, and identifies some open research problems that represent the most interesting areas of contribution.

The multiparty nature of multicast applications presents new challenges for Mobile IP users. Unfortunately, when a multicast receiver is mobile, it will experience additional delay in receiving multicast packets due to handover delay, join latency, and increased propagation delay to the new location. In this paper we propose a new solution to avoid the multicast triangle routing problem inside the home network when the Mobile IP bidirectional tunnelling approach is used. Our solution is based on the use of a new architectural entity called "Multicast Router Proxy". The proxy is used to redirect multicast traffic to the mobile receiver and avoid redundant multicast traffic passage to the Home Agent. In addition, we enhance the functionalities of the Home Agent to efficiently manage the multicast membership information for mobile receivers that are located outside the home network.

Security and QoS are two main issues for a successful wide deployment of multicast services. For instance, in a multicast streaming application, a receiver would require a data origin authentication service as well as a quality adaptation technique for the received stream. Signature propagation and layered multicast are efficient solutions satisfying these two requirements. In this paper we investigate the use of signature propagation to ensure data origin authentication service. We, then, propose a set of novel data origin authentication techniques for layered media-streaming video. In addition to data origin authentication, the proposed techniques offer continuous non-repudiation of the origin and data integrity. These techniques take advantage of the preestablished layered structure of the encoded video data to reduce the overhead and improve the overall verification in lossy network environments. We evaluate the performance of the proposed techniques through extensive simulations using NS2 simulator.

While the Mobile IP protocol does not exclude the use of multiple Home Agents (HAs), it does not impose any particular model either. Recent solutions propose that a mobile node uses multiple HAs located in different physical links in his home network. However, no architectural scheme is proposed either for unicast or multicast communications. In this paper, we propose a Hierarchical Home Agent architecture in which each Home Agent (HA) is assigned a specific topological level in its domain. The mobile node is notified about such hierarchy and chooses the closest HA on a perconnection basis. Our primary goal is to optimise both unicast and multicast routing for mobile nodes. We prove that our solution avoids redundant multicast traffic in the home domain and it is easy to implement using the current Mobile IP specification without extra cost.

IP multicast was initially designed for stationary members and does not consider extra requirements for mobile parties. In fact, to deploy IP multicast, two essential components are required: a membership management protocol to manage the join/leave process, and a routing protocol to build the multicast delivery tree. Currently, multicast membership protocols such as IGMPv3 and MLDv2 rely on a periodic forwarding model between the Querier and the receivers. However, when dealing with mobile IP receivers, the periodic queries prohibit mobile hosts from using sleep mode to conserve battery power when no multicast traffic is present. In addition, the home agent (HA) has to implement the IGMP/MLD forwarding functions, and to tunnel periodically membership messages to all remote mobile receivers, which induces a significant processing overhead. To solve this problem, we propose an adaptive solution in which the HA does not periodically transmit membership messages to mobile receiver. We prove by simulation that our solution reduces significantly the amount of membership messages sent through the mobile IP bi-directional tunnel

Even though hierarchical group communication is a prominent communication model for a variety of applications, featured by hierarchical communication rules, it has not been sufficiently investigated in the security literature. In this paper, we introduce private hierarchical group communication and we determine its specific confidentiality requirements, and then we propose an efficient key management protocol satisfying those requirements. This work is done in the frame of a national french project whose consortium includes the international telecom company EADS, INRIA, CNRS and ENST-Paris. The project is called Safe- Cast and deals with group communication in PMR networks that are used mainly by security corps (police, fire fighters, soldiers, and so forth) in areas where it is difficult to have network infrastructures, such as war battles or following a natural disaster (earthquake, tsunami, tornado, or similar).

Abstract Leader election in a network plays an important role in the area of distributed algorithm design. Structural properties of the network as well as presence of direction on the edges of the network greatly affects the complexity of the leader election problem, which is primarily measured by the message complexity of the protocol. Our purpose in the present article is to adapt the existing distributed match making concepts to design a linear time leader election algorithm for star graphs. Star graphs have been extensively studied as an attractive alternative for the well‐known hypercubes for network design. Linear election algorithms for oriented hypercubes is known; no such algorithm exists for oriented star graphs. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 45(2), 169–179 2005

Many group-oriented applications require authenticating the source of the received traffic, such as broadcasting stock quotes and video-conferencing and hence source authentication is an important component in the whole multicast security architecture. Multicast source authentication must take into consideration the scalability and the efficiency of the underlying cryptographic schemes and mechanisms, because multicast groups can be very large and the exchanged data is likely to be important in volume (streaming). Besides, multicast source authentication must be robust enough against packet loss because most of multicast multimedia applications do not use reliable packet delivery. We propose a new adaptive and efficient source authentication protocol which tolerates packet loss and guarantees nonrepudiation for multicast flows. We have simulated our protocol using NS-2, and the simulation results show that the protocol has remarkable features and efficiency compared to other recent source authentication protocols.

We propose a multicast source authentication protocol based on a novel layered hash-chaining scheme. We called this protocol: receiver driven layered hash-chaining for multicast source authentication (RLH). This protocol tolerates packet loss and guarantees nonrepudiation of media-streaming origin. RLH allows us to save bandwidth as shown in the simulation results section.

This paper considers the problem of fault-tolerance and built-in robustness in key agreement for dynamic peer groups. A fault-tolerant key establishment protocol is developed by extending the group Diffie-Hellman key agreement protocol to support asynchronous settings and faulty participants. The protocol uses recent results on failure detection in asynchronous distributed systems. Simulation results show that the key agreement protocol augmented with failure detection increases significantly the number of group members that participate in the computation of the group key while introducing a low message overhead.

Smooth handoff was introduced in mobile IP to overcome this problem of packet loss during handoff. However, smooth handoff causes packets sequence disruption during packet forwarding procedure, which may result in degradation of network performance in higher layer protocol. In this paper, we discuss the impact of receiving out-of-sequence packets by the mobile node on TCP and UDP applications and we propose a technique, which minimizes the arrival of out-of-sequence packets to the mobile node. This technique anticipates forwarding of packets from the current foreign agent to the new one while the mobile node initiates its handoff. To evaluate our solution, we use the unstable time period (UTP) when the packet sequence could be mis-ordered. We show that the unstable period in our solution is very low than the unstable time period in classical smooth handoff. Furthermore, we also show that our solution reduces the considerably out-of-sequence packets generated by smooth handoff.

IP multicast is increasingly used as an efficient communication mechanism for group-oriented applications on the Internet. This success urged the development of security mechanisms for that communication model. A common drawback of the proposed solutions is that they do not take into consideration the dynamicity of group members. This leads to inefficient solutions for real multicast sessions. In this paper, we first classify proposed protocols for secure multicast and point out their non-suitability for dynamic groups. We then propose an efficient protocol, called AKMP, which maintains good performance by adapting the key management process to the membership frequency during the multicast session. Simulation results show that our protocol is more efficient than existing protocols.

It is now well recognised that the consensus problem is a fundamental problem when one has to implement fault-tolerant distributed services. We extend the consensus paradigm to asynchronous distributed mobile systems prone to disconnection and process crash failures. The paper, first, shows that a consensus problem between mobile hosts is reducible to two agreement problems (a consensus problem and a group membership problem) between fixed hosts. Then, following an approach investigated by Guerraoui and Schiper (see IEEE Transactions on Software Engineering, vol.27, no.1, p.29-41, 2001), the paper uses a genetic consensus service as a basic building block to construct a modular and simple solution.

In this paper we propose a framework for a simple resource reservation protocol for multicast communications in the Internet. In contrast to RSVP, where heavy setup mechanisms are used, our protocol is traffic driven and does not use special messages for resource reservation, refresh or release. The reservation session is managed by the flow data packets themselves. Our protocol is suitable for resource reservation in dynamic and rearrangeable multicast environments. It also tolerates nodes and links failures by instantaneously allowing a new resource reservation on alternative paths.

Resource reservation protocols allow communicating hosts to reserve resources such as bandwidth to offer a guaranteed service. Distributed applications like multimedia and teleconferencing are immediate applications of resource reservation. We propose a simple resource reservation protocol. This protocol does not use special reservation and release messages, nor refresh messages as in RSVP. It is flow-dedicated based. It tolerates also node or link failure by using an alternate path which satisfies the needed resources.

In this paper we present a multicast protocol for building and maintaining delay-constrained multicast shared trees (DCMST). Our protocol is based on the search of available delay-constrained multipath to graft a new receiver to the shared tree. The new receiver chooses the most promising route regarding to its available bandwidth. This way we help the equilibrium of charge on the network and we offer better routes for resource reservation. In dynamic source groups the DCMST may need to be frequently updated to satisfy the delay constraint; our protocol incorporates a least-cost updating mechanism. The proposed protocol scales well due to the reduced search phase which is limited to available links only.

Abstract For a given graph G of order n, a routing R is a set of n(n − 1) elementary paths specified for every ordered pair of vertices in G. The edge forwarding index of a network (G,R), denoted π(G,R) is the maximum number of paths of R going through any edge e of G. The edge forwarding index of G, denoted π(G), is the minimum of π(G,R) taken over all the possible routings R of G. Given n ≤ 15 and Δ ≤ n − 1 we determine πΔ,n, the minimum of π(G) taken over all graphs G of order n with maximum degree at most Δ. This is known as the edge forwarding index problem. © 1993 by John Wiley & Sons, Inc.