While the integration of the Internet of Things (IoT) has expanded networking capabilities, it has also intensified challenges regarding communication reliability and resource constraints in wireless environments. Interference and message collisions significantly impact fault tolerance and energy efficiency, particularly in distance-2 colored networks. While traditional TDMA-based MAC schemes mitigate collisions, they often leave a gap in performance due to underutilized time slots. This paper bridges that gap by unveiling an incisive study on harnessing underused time slots to bolster both communication and energy efficiency in wireless networks. Our new distributed protocol—operating within the synchronous distance-2 colored broadcast/receive model—empowers highly active nodes to judiciously borrow time slots from underutilized neighbors while preserving collision-free and conflict-free guarantees. Furthermore, we introduce a nuanced probability-based strategy that enables nodes to discern opportune moments for lending their time slots. Experimental results substantiate the efficacy of our proposed solution, offering a pathway toward optimizing wireless network operations in the IoT era.

In large-scale resource-constrained wireless networks, such as those prevalent in the Internet of Things (IoT), efficient communication scheduling remains a critical challenge. Among the various approaches, Time Division Multiple Access (TDMA) protocols have been widely adopted for their structured and collision-free communication capabilities. Nevertheless, despite extensive research in this area, current solutions often exhibit suboptimal performance, particularly in dynamic environments where node activity levels fluctuate over time.This paper introduces a novel fully distributed TDMA-based scheduling protocol that intelligently maximizes the utilization of communication resources. The proposed approach adaptively reallocates underutilized time slots, originally assigned to temporarily inactive nodes, to those experiencing higher communication demands. This dynamic reallocation not only improves channel utilization but also reduces idle periods, thereby enhancing overall network efficiency. To further enhance performance, we incorporate a lightweight probabilistic mechanism that governs the temporal leasing of unused slots. This mechanism balances the trade-off between slot availability and transmission reliability, minimizing packet loss while preserving fairness and stability within the network.Simulations across a range of network scenarios demonstrate that our protocol significantly improves throughput, latency, and reliability in resource-constrained environments. These results highlight the protocol’s potential as a robust and scalable solution for adaptive and energy-efficient scheduling in next-generation IoT networks.

The convergence of Software-Defined Networking (SDN) and Blockchain technologies has emerged as a promising solution for addressing critical challenges in Internet of Things (IoT) networks. This paper presents a comprehensive review of recent research papers exploring the integration of SDN and Blockchain to enhance the security, scalability, and efficiency of IoT ecosystems. The surveyed literature highlights diverse architectures, algorithms, and frameworks proposed to tackle various IoT-related challenges, ranging from data security and privacy to energy efficiency and resource management. Through structured summaries and comparative analyses, this study elucidates the evolving trends in the interdisciplinary domain of SDN-Blockchain integration for IoT networks, identifying key research gaps and future directions. Moreover, the paper discusses the benefits, challenges, and considerations associated with this convergence, offering insights into optimizing consensus mechanisms, leveraging edge computing, standardizing interoperable protocols, enhancing privacy-preserving technologies, and fostering cross-disciplinary collaborations. In conclusion, while acknowledging the transformative potential of SDN-Blockchain integration in shaping the future of interconnected smart ecosystems, this paper underscores the importance of concerted research efforts and collaborative initiatives to address the multifaceted challenges and realize the full potential of this convergence.

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.

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.

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.

5G is the fifth generation technology standard for cellular networks, which is already being deployed and offering many advantages for communications, such as the high degree of flexibility, the possibility of management and control of systems and resources, thus allowing to host and execute services in one or more distinct network slices, etc. Non-orthogonal multiple access (NOMA) is being considered as a key enabling technique for 5G cellular systems. The earlier generations are becoming less practical with the emergent requirements such as very high spectral efficiency, very low latency, supporting diverse quality of services (QoS). Researchers are working on different techniques to fulfill these requirements, and NOMA is one of the essentials due to its capacity to increase spectrum efficiency. NOMA schemes exploit channel gain differences to serve multiple users concurrently, by superimposing multiple users' information signals at the transmitter side. In this paper, we review, analyze and classify recent papers on resource allocation problem in 5G networks, and then we discuss the proposed solutions. In particular, the papers are classified into two main categories: power/energy-efficient and rate-optimal. For each paper, the objective, optimization method and main results are discussed. Finally, some open challenges are highlighted.

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 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.

This paper considers distributed vertex-coloring in broadcast/receive networks suffering from conflicts and collisions. (A collision occurs when, during the same round, messages are sent to the same process by too many neighbors; a conflict occurs when a process and one of its neighbors broadcast during the same round.) More specifically, the paper focuses on multi-channel networks, in which a process may either broadcast a message to its neighbors or receive a message from at most γ of them. The paper first provides a new upper bound on the corresponding graph coloring problem (known as frugal coloring) in general graphs, proposes an exact bound for the problem in trees, and presents a deterministic, parallel, color-optimal, collision- and conflict-free distributed coloring algorithm for trees, and proves its correctness.

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.

Internet of Things (IoT) is a network composed of a variety of heterogeneous things and objects such as Connected Wearable Devices (sensors, MEMS, microrobots, PDA, ...), Connected Cars, Connected Homes, Connected Cities, and the Industrial Internet. These things use generally wireless communication to interact and cooperate with each other to reach common services and goals. IoT(T, n) is a wireless network of things composed of T things with n items (information) distributed on it. The aim of the permutation routing is to route to each thing, its items, so it can accomplish its task. In this paper, we present an agent-based broadcast protocol for mobile Internet of Things that uses few communication channels. The main idea is to partition things into groups according to the number of channels. In each group, an agent manages a set of things. This new protocol performs efficiently with respect to the number of broadcast rounds and runs without conflict and collision on the communication channels. We give an estimation of the upper and the lower bounds of the number of broadcast rounds in the worst case. This paper is the first to present efficient broadcast protocol for the internet of things.

This article is on message-passing systems where communication is (a) synchronous and (b) based on the "broadcast/receive" pair of communication operations. "Synchronous" means that time is discrete and appears as a sequence of time slots (or rounds) such that each message is received in the very same round in which it is sent. "Broadcast/receive" means that during a round a process can either broadcast a message to its neighbors or receive a message from one of them. In such a communication model, no two neighbors of the same process, nor a process and any of its neighbors, must be allowed to broadcast during the same time slot (thereby preventing message collisions in the first case, and message conflicts in the second case). From a graph theory point of view, the allocation of slots to processes is known as the distance-2 coloring problem: a color must be associated with each process (defining the time slots in which it will be allowed to broadcast) in such a way that any two processes at distance at most 2 obtain different colors, while the total number of colors is "as small as possible". The paper presents a parallel message-passing distance-2 coloring algorithm suited to trees, whose roots are dynamically defined. This algorithm, which is itself collision-free and conflict-free, uses Δ+1 colors where Δ is the maximal degree of the graph (hence the algorithm is color-optimal). It does not require all processes to have different initial identities, and its time complexity is O(dΔ), where Δ is the depth of the tree. As far as we know, this is the first distributed distance-2 coloring algorithm designed for the broadcast/receive round-based communication model, which owns all the previous properties.

Programmable matter i.e. matter that can change its physical properties, more likely its shape according to an internal or an external action is a good example of a cybermatics component. As it links a cyberized shape to real matter, it is a straight example of cyber-physical conjugation. But, this interaction between virtual and real worlds needs two elements. The first one is to find a way to represent the cyberized object using programmable matter and the second is to be able to adapt the matter to the cyberized changes. This article presents the progresses made in these two topics within the Claytronics project.

In this paper we propose a distributed and robust parallel redeployment algorithm for MEMS micro robots. MEMS micro robots are low-power and low-memory capacity devices that can sense and act. To deal with the MEMS micro robots characteristics, in this paper, we present an efficient redeployment algorithm without predefined positions of the target shape, which reduces the memory usage to a constant complexity. This algorithm optimizes the energy consumption by minimizing the amount of displacement and the number of messages. This solution improves the memory usage (number of states), the execution time and the number of movements by using movement of different micro robots at the same time. In addition, we show how to predict the number of movement for each node to make the algorithm robust.

In this paper we propose a distributed and efficient parallel self-reconfiguration algorithm for MEMS microrobots. MEMS microrobots perform various missions and tasks in a wide range of applications including odor localization, firefighting, medical service, surveillance and security, and search and rescue. To achieve these tasks the self-reconfiguration for MEMS microrobots is required. The self-reconfiguration with shared map does not scale. Because with the map (predefined positions of the target shape) each node should store all predefined positions of the target shape, therefore this is not always possible as MEMS nodes have a low-memory capacity. In this paper, we present an efficient self-reconfiguration algorithm without predefined positions of the target shape, which reduces the memory usage to a constant complexity. This algorithm improves the energy consumption by minimizing the amount of displacement and the number of messages.

MEMS micro robots are low-power and low memory capacity devices that can sense and act. One of the most challenges in MEMS micro robot applications is the self-reconfiguration, especially when the efficiency and the scalability of the algorithm are required. In the literature, if we want a self-reconfiguration of micro robots to a target shape consisting of P positions, each micro robot should have a memory capacity of P positions. Therefore, if P equals to millions, each node should have a memory capacity of millions of positions. Therefore, this is not scalable. In this paper, nodes do not record any position, we present a self-reconfiguration method where a set of micro robots are unaware of their current position and do not have the map of the target shape. In other words, nodes do not store the positions that build the target shape. Consequently, memory usage for each node is reduced to O(1). An algorithm of self-reconfiguration to optimize the communication is deeply studied showing how to manage the dynamicity (wake up and sleep of micro robots) of the network to save energy. Our algorithm is implemented in Meld, a declarative language, and executed in a real environment simulator called DPRSim.