Biblio

Wireless mesh networks (WMNs) are dynamically self-organized and self-configured technology ensuring efficient connection to Internet. Such networks suffer from many issues, like lack of performance efficiency when huge amount of traffic are injected inside the networks. To deal with such issues, we propose in this paper an adapted fuzzy framework; by monitoring the rate of change in queue length in addition to the current length of the queue, we are able to provide a measure of future queue state. Furthermore, by using explicit rate messages we can make node sources more responsive to unexpected changes in the network traffic load. The simulation results show the efficiency of the proposed model.

Wireless Mesh Networks (WMN) are becoming inevitable in this world of high technology as it provides low cost access to broadband services. Moreover, the technologists are doing research to make WMN more reliable and secure. Subsequently, among wireless ad-hoc networking technologies, Bluetooth Low Energy (BLE) is gaining high degree of importance among researchers due to its easy availability in the gadgets and low power consumption. BLE started its journey from version 4.0 and announced the latest version 5 with mesh support capability. BLE being a low power and mesh supported technology is nowadays among the hot research topics for the researchers. Many of the researchers are working on BLE mesh technology to make it more efficient and smart. Apart from other variables of efficiency, like all communication networks, mesh network security is also of a great concern. In view of the aforesaid, this paper provides a comprehensive review on several works associated to the security in WMN and BLE mesh networks and the research related to the BLE security protocols. Moreover, after the detailed research on related works, this paper has discussed the pros and cons of the present developed mesh security mechanisms. Also, at the end after extracting the curx from the present research on WMN and BLE mesh security, this research study has devised some solutions as how to mitigate the BLE mesh network security lapses.

In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.

Permissioned Blockchain (PBC) has become a prevalent data structure to ensure that the records are immutable and secure. However, PBC still has significant challenges before it can be realized in different applications. One of such challenges is the overhead of the communication which is required to execute the Byzantine Agreement (BA) protocol that is needed for consensus building. As such, it may not be feasible to implement PBC for resource constrained environments such as Internet-of-Things (IoT). In this paper, we assess the communication overhead of running BA in an IoT environment that consists of wireless nodes (e.g., Raspberry PIs) with meshing capabilities. As the the packet loss ratio is significant and makes BA unfeasible to scale, we propose a network coding based approach that will reduce the packet overhead and minimize the consensus completion time of the BA. Specifically, various network coding approaches are designed as a replacement to TCP protocol which relies on unicasting and acknowledgements. The evaluation on a network of Raspberry PIs demonstrates that our approach can significantly improve scalability making BA feasible for medium size IoT networks.

We propose a Centralized Tree based Diffie-Hellman (CTDH) protocol for wireless mesh networks, which take into account the characteristics of mesh network operations, wireless routers and mobile devices. Performance analysis shows that CTDH is more efficient than the Tree-Based Group Diffie-Hellman Protocol (TGDH).

The ability to transmit high volumes of data over a long distance makes WiFi mesh networks an ideal transmission solution for remote video surveillance. Instead of independently manipulating the node deployment, channel and interface assignment, and routing to improve the network performance, we propose a joint network design using multi-objective genetic algorithm to take into account the interplay of them. Moreover, we found a performance evaluation method based on the transmission capability of the WiFi mesh networks for the first time. The good agreement of our obtained multiple optimized solutions to the extensive simulation results by NS-3 demonstrates the effectiveness of our design.

Cognitive Radio (CR) has garnered much attention in the last decade, while the security issues are not fully studied yet. Existing research on attacks and defenses in CR - based networks focuses mostly on individual network layers, whereas cross-layer attacks remain fortified against single-layer defenses. In this paper, we shed light on a new vulnerability in cross-layer routing protocols and demonstrate how a perpetrator can exploit this vulnerability to manipulate traffic flow around it. We propose this cross-layer attack in CR-based wireless mesh networks (CR-WMNs), which we call off-sensing and route manipulation (OS-RM) attack. In this cross-layer assault, off-sensing attack is launched at the lower layers as the point of attack but the final intention is to manipulate traffic flow around the perpetrator. We also introduce a learning strategy for a perpetrator, so that it can gather information from the collaboration with other network entities and capitalize this information into knowledge to accelerate its malice intentions. Simulation results show that this attack is far more detrimental than what we have experienced in the past and need to be addressed before commercialization of CR-based networks.

Wireless mesh networking (WMN) is a new technology aimed to introduce the benefits of using multi-hop and multi-path to the wireless world. However, the absence of a fast and reliable handoff protocol is a major drawback especially in a technology designed to feature high mobility and scalability. We propose a fast and efficient handoff authentication protocol for wireless mesh networks. It is a token-based authentication protocol using pre-distributed parameters. We provide a performance comparison among our protocol, UFAP, and other protocols including EAP-TLS and EAP-PEAP tested in an actual setup. Performance analysis will prove that our proposed handoff authentication protocol is 250 times faster than EAP-PEAP and 500 times faster than EAP-TLS. The significant improvement in performance allows UFAP to provide seamless handoff and continuous operation even for real-time applications which can only tolerate short delays under 50 ms.

As wireless mesh networks (WMNs) develop rapidly, security issue becomes increasingly important. Intrusion Detection System (IDS) is one of the crucial ways to detect attacks. However, IDS in wireless networks including WMNs brings high detection overhead, which degrades network performance. In this paper, we apply compressed sensing (CS) theory to IDS and propose a CS based IDS for hybrid WMNs. Since CS can reconstruct a sparse signal with compressive sampling, we process the detected data and construct sparse original signals. Through reconstruction algorithm, the compressive sampled data can be reconstructed and used for detecting intrusions, which reduces the detection overhead. We also propose Active State Metric (ASM) as an attack metric for recognizing attacks, which measures the activity in PHY layer and energy consumption of each node. Through intensive simulations, the results show that under 50% attack density, our proposed IDS can ensure 95% detection rate while reducing about 40% detection overhead on average.

Wireless mesh networks (WMNs) are known for possessing good attributes such as low up-front cost, easy network maintenance, and reliable service coverage. This has largely made them to be adopted in various environments such as; school campus networks, community networking, pervasive healthcare, office and home automation, emergency rescue operations and ubiquitous wireless networks. The routing nodes are equipped with self-organized and self-configuring capabilities. However, the routing mechanisms of WMNs depend on the collaboration of all participating nodes for reliable network performance. The authors of this paper have noted that most routing algorithms proposed for WMNs in the last few years are designed with the assumption that all the participating nodes will collaboratively be involved in relaying the data packets originated from a source to a multi-hop destination. Such design approach however exposes WMNs to vulnerability such as malicious packet drop attack. This paper presents an evaluation of the effect of the black hole attack with other influential factors in WMNs. In this study, NS-3 simulator was used with AODV as the routing protocol. The results show that the packet delivery ratio and throughput of WMN under attack decreases sharply as compared to WMN free from attack. On an average, 47.41% of the transmitted data packets were dropped in presence of black hole attack.

Wireless Mesh Network (WMN) is a promising networking technology, which is cost effective, robust, easily maintainable and provides reliable service coverage. WMNs do not rely on a centralized administration and have a distributed nature in which nodes can participate in routing packets. Such design and structure makes WMNs vulnerable to a variety of security threats. Therefore, to ensure secure route discovery in WMNs, we propose a trust model which is based on Evidence- Based Subjective Logic (EBSL). The proposed trust model computes trust values of individual nodes and manages node reputation. We use watchdog detection mechanism to monitor selfish behavior in the network. A node's final trust value is calculated by aggregating the nodes direct and recommendation trust information. The proposed trust model ensures secure routing of packets by avoiding paths with untrusted nodes. The trust model is able to detect selfish behavior such as black-hole and gray-hole attacks.

Because major smartphone platforms are equipped with Bluetooth Low Energy (BLE) capabilities, more and more smart devices have adopted BLE technologies to communicate with smartphones. In order to support the mesh topology in BLE networks, several proposals have been designed. Among them, the Bluetooth Special Interest Group (SIG) recently released a specification for Bluetooth mesh networks based upon BLE technology. This paper focuses on this standard solution and analyses its security protocol with hardware security in mind. As it is expected that internet of things (IoT) devices will be deployed everywhere, the risk of physical attacks must be assessed. First, we provide a comprehensive survey of the security features involved in Bluetooth mesh. Then, we introduce some physical attacks identified as serious threats for the IoT and discuss their relevance in the case of Bluetooth mesh networks. Finally, we briefly discuss possible countermeasures to reach a secure implementation.

In modern cyber-physical systems and wireless sensor networks the complexity of crisis management processes is caused by a variety of software/hardware assets and communication protocols, the necessity of their collaborative function, possible inconsistency of data flows between particular devices and increased requirements to cyber-physical security. A crisis management oriented model of a communicational mobile network is constructed. A general architecture of network nodes by the use of XBee circuits, Arduino microcontrollers and connecting equipment are developed. An analysis of possible cyber-physical security events on the base of existing intruder models is performed. A series of experiments on modeling attacks on network nodes is conducted. Possible ways for attack revelations by means of components for security event collection and data correlation is discussed.

Advanced Metering Infrastructure (AMI) forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication within an AMI needs to be secure, key management becomes an issue due to overhead and limited resources. While using public-keys eliminate some of the overhead of key management, there is still challenges regarding certificates that store and certify the public-keys. In particular, distribution and storage of certificate revocation list (CRL) is major a challenge due to cost of distribution and storage in AMI networks which typically consist of wireless multi-hop networks. Motivated by the need of keeping the CRL distribution and storage cost effective and scalable, in this paper, we present a distributed CRL management model utilizing the idea of distributed hash trees (DHTs) from peer-to-peer (P2P) networks. The basic idea is to share the burden of storage of CRLs among all the smart meters by exploiting the meshing capability of the smart meters among each other. Thus, using DHTs not only reduces the space requirements for CRLs but also makes the CRL updates more convenient. We implemented this structure on ns-3 using IEEE 802.11s mesh standard as a model for AMI and demonstrated its superior performance with respect to traditional methods of CRL management through extensive simulations.

With the advancement of unmanned aerial vehicles (UAV), 3D wireless mesh networks will play a crucial role in next generation mission critical wireless networks. Along with providing coverage over difficult terrain, it provides better spectral utilization through 3D spatial reuse. However, being a wireless network, 3D meshes are vulnerable to jamming/disruptive attacks. A jammer can disrupt the communication, as well as control of the network by intelligently causing interference to a set of nodes. This paper presents a distributed mechanism of avoiding jamming attacks by means of 3D spatial filtering where adaptive beam nulling is used to keep the jammer in null region in order to bypass jamming. Kalman filter based tracking mechanism is used to estimate the most likely trajectory of the jammer from noisy observation of the jammer's position. A beam null border is determined by calculating confidence region of jammer's current and next position estimates. An optimization goal is presented to calculate optimal beam null that minimizes the number of deactivated links while maximizing the higher value of confidence for keeping the jammer inside the null. The survivability of a 3D mesh network with a mobile jammer is studied through simulation that validates an 96.65% reduction in the number of jammed nodes.

Community detection is an advanced graph operation that is used to reveal tightly-knit groups of vertices (aka. communities) in real-world networks. Given the intractability of the problem, efficient heuristics are used in practice. Yet, even the best of these state-of-the-art heuristics can become computationally demanding over large inputs and can generate workloads that exhibit inherent irregularity in data movement on manycore platforms. In this paper, we posit that effective acceleration of the graph community detection operation can be achieved by reducing the cost of data movement through a combined innovation at both software and hardware levels. More specifically, we first propose an efficient software-level parallelization of community detection that uses approximate updates to cleverly exploit a diminishing returns property of the algorithm. Secondly, as a way to augment this innovation at the software layer, we design an efficient Wireless Network on Chip (WiNoC) architecture that is suited to handle the irregular on-chip data movements exhibited by the community detection algorithm under both unicast- and broadcast-heavy cache coherence protocols. Experimental results show that our resulting WiNoC-enabled manycore platform achieves on average 52% savings in execution time, without compromising on the quality of the outputs, when compared to a traditional manycore platform designed with a wireline mesh NoC and running community detection without employing approximate updates.

In low-power wireless networking, new applications such as cooperative robots or industrial closed-loop control demand for network-wide consensus at low-latency and high reliability. Distributed consensus protocols is a mature field of research in a wired context, but has received little attention in low-power wireless settings. In this paper, we present A2: Agreement in the Air, a system that brings distributed consensus to low-power multi-hop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this reliable base layer and enables the two- and three-phase commit protocols, as well as network services such as group membership, hopping sequence distribution and re-keying. We evaluate A2 on four public testbeds with different deployment densities and sizes. A2 requires only 475 ms to complete a two-phase commit over 180 nodes. The resulting duty cycle is 0.5% for 1-minute intervals. We show that A2 achieves zero losses end-to-end over long experiments, representing millions of data points. When adding controlled failures, we show that two-phase commit ensures transaction consistency in A2 while three-phase commit provides liveness at the expense of inconsistency under specific failure scenarios.

With the advance of fifth generation (5G) networks, network density needs to grow significantly in order to meet the required capacity demands. A massive deployment of small cells may lead to a high cost for providing fiber connectivity to each node. Consequently, many small cells are expected to be connected through wireless links to the umbrella eNodeB, leading to a mesh backhaul topology. This backhaul solution will most probably be composed of high capacity point-to-point links, typically operating in the millimeter wave (mmWave) frequency band due to its massive bandwidth availability. In this paper, we propose a mathematical model that jointly solves the user association and backhaul routing problem in the aforementioned context, aiming at the energy efficiency maximization of the network. Our study considers the energy consumption of both the access and backhaul links, while taking into account the capacity constraints of all the nodes as well as the fulfillment of the service-level agreements (SLAs). Due to the high complexity of the optimal solution, we also propose an energy efficient heuristic algorithm (Joint), which solves the discussed joint problem, while inducing low complexity in the system. We numerically evaluate the algorithm performance by comparing it not only with the optimal solution but also with reference approaches under different traffic load scenarios and backhaul parameters. Our results demonstrate that Joint outperforms the state-of-the-art, while being able to find good solutions, close to optimal, in short time.

Software Defined Radio (SDR) can move the complicated signal processing and handling procedures involved in communications from radio equipment into computer software. Consequently, SDR equipment could consist of only a few chips connected to an antenna. In this paper, we present an implemented SDR testbed, which consists of four complete SDR nodes. Using the designed testbed, we have conducted two case studies. The first is designed to facilitate video transmission via adaptive LTE links. Our experimental results demonstrate that adaptive LTE link video transmission could reduce the bandwidth usage for data transmission. In the second case study, we perform UE location estimation by leveraging the signal strength from nearby cell towers, pertinent to various applications, such as public safety and disaster rescue scenarios where GPS (Global Position System) is not available (e.g., indoor environment). Our experimental results show that it is feasible to accurately derive the location of a UE (User Equipment) by signal strength. In addition, we design a Hardware In the Loop (HIL) simulation environment using the Vienna LTE simulator, srsLTE library, and our SDR testbed. We develop a software wrapper to connect the Vienna LTE simulator to our SDR testbed via the srsLTE library. Our experimental results demonstrate the comparative performance of simulated UEs and eNodeBs against real SDR UEs and eNodeBs, as well as how a simulated environment can interact with a real-world implementation.

The high mobility of Army tactical networks, combined with their close proximity to hostile actors, elevates the risks associated with short-range network attacks. The connectivity model for such short range connections under active operations is extremely fluid, and highly dependent upon the physical space within which the element is operating, as well as the patterns of movement within that space. To handle these dependencies, we introduce the notion of "key cyber-physical terrain": locations within an area of operations that allow for effective control over the spread of proximity-dependent malware in a mobile tactical network, even as the elements of that network are in constant motion with an unpredictable pattern of node-to-node connectivity. We provide an analysis of movement models and approximation strategies for finding such critical nodes, and demonstrate via simulation that we can identify such key cyber-physical terrain quickly and effectively.

In Advanced Metering Infrastructure (AMI) networks, power data collections from smart meters are static. Due to such static nature, attackers may predict the transmission behavior of the smart meters which can be used to launch selective jamming attacks that can block the transmissions. To avoid such attack scenarios and increase the resilience of the AMI networks, in this paper, we propose dynamic data reporting schedules for smart meters based on the idea of moving target defense (MTD) paradigm. The idea behind MTD-based schedules is to randomize the transmission times so that the attackers will not be able to guess these schedules. Specifically, we assign a time slot for each smart meter and in each round we shuffle the slots with Fisher-Yates shuffle algorithm that has been shown to provide secure randomness. We also take into account the periodicity of the data transmissions that may be needed by the utility company. With the proposed approach, a smart meter is guaranteed to send its data at a different time slot in each round. We implemented the proposed approach in ns-3 using IEEE 802.11s wireless mesh standard as the communication infrastructure. Simulation results showed that our protocol can secure the network from the selective jamming attacks without sacrificing performance by providing similar or even better performance for collection time, packet delivery ratio and end-to-end delay compared to previously proposed protocols.

Using mobile sinks to collect sensed data in WSNs (Wireless Sensor Network) is an effective technique for significantly improving the network lifetime. We investigate the problem of collecting sensed data using a mobile sink in a WSN with unreachable regions such that the network lifetime is maximized and the total tour length is minimized, and propose a polynomial-time heuristic, an ILP-based (Integer Linear Programming) heuristic and an MINLP-based (Mixed-Integer Non-Linear Programming) algorithm for constructing a shortest path routing forest for the sensor nodes in unreachable regions, two energy-efficient heuristics for partitioning the sensor nodes in reachable regions into disjoint clusters, and an efficient approach to convert the tour construction problem into a TSP (Travelling Salesman Problem). We have performed extensive simulations on 100 instances with 100, 150, 200, 250 and 300 sensor nodes in an urban area and a forest area. The simulation results show that the average lifetime of all the network instances achieved by the polynomial-time heuristic is 74% of that achieved by the ILP-based heuristic and 65% of that obtained by the MINLP-based algorithm, and our tour construction heuristic significantly outperforms the state-of-the-art tour construction heuristic EMPS.

Multi-hop Wireless Mesh Networks (WMNs) is a promising new technique for communication with routing protocol designs being critical to the effective and efficient of these WMNs. A common approach for routing traffic in these networks is to select a minimal distance from source to destination as in wire-line networks. Opportunistic Routing(OR) makes use of the broadcasting ability of wireless network and is especially very helpful for WMN because all nodes are static. Our proposed scheme of Multicast Opportunistic Routing(MOR) in WMNs is based on the broadcast transmissions and Learning Au-tomata (LA) to expand the potential candidate nodes that can aid in the process of retransmission of the data. The receivers are required to be in sync with one another in order to avoid duplicated broadcasting of data which is generally achieved by formulating the forwarding candidates according to some LA based metric. The most adorable aspect of this protocol is that it intelligently "learns" from the past experience and improves its performance. The results obtained via this approach of MOR, shows that the proposed scheme outperforms with some existing sachems and is an improved and more effective version of opportunistic routing in mesh network.

This paper discusses two issues with multi-channel multi-radio Wireless Mesh Networks (WMN): gateway placement and gateway selection. To address these issues, a method will be proposed that places gateways at strategic locations to avoid congestion and adaptively learns to select a more efficient gateway for each wireless router by using learning automata. This method, called the N-queen Inspired Gateway Placement and Learning Automata-based Selection (NQ-GPLS), considers multiple metrics such as loss ratio, throughput, load at the gateways and delay. Simulation results from NS-2 simulator demonstrate that NQ-GPLS can significantly improve the overall network performance compared to a standard WMN.

Wireless mesh network (WMN) consists of mesh gateways, mesh routers and mesh clients. In hybrid WMN, both backbone mesh network and client mesh network are mesh connected. Capacity analysis of multi-hop wireless networks has proven to be an interesting and challenging research topic. The capacity of hybrid WMN depends on several factors such as traffic model, topology, scheduling strategy and bandwidth allocation strategy, etc. In this paper, the capacity of hybrid WMN is studied according to the traffic model and bandwidth allocation. The traffic of hybrid WMN is categorized into internal and external traffic. Then the capacity of each mesh client is deduced according to appropriate bandwidth allocation. The analytical results show that hybrid WMN achieves lower capacity than infrastructure WMN. The results and conclusions can guide for the construction of hybrid WMN.