Unreliable Links Research Articles

A secure multipath reactive protocol for routing in IoT and HANETs

In numerous Internet of Things (IoT) scenarios (such as Intelligent Transportation System (ITS) or environment sensing), the ad hoc mode is widely used. Ad-hoc networks have several benefits including infrastructureless and spontaneous deployment, and the opportunity to set up temporary and dynamic networks cost-effectively. However, some of their characteristics such as the unreliability of wireless links, dynamic topology and resource constraints in energy and processing power of objects, make new protocols’ development ignore security requirements of applications in order to satisfy some quality of service. Consequently, there is a lack of standardization works in the field of secure routing among IoT devices. Furthermore, recently proposed secure routing approaches (mostly from the academic community) do not meet the current needs and requirements of secure routing for IoT applications. In this context, we propose a lightweight and secure routing scheme that combines multipath routing and trust management, that can adapt to different scenarios in the IoT environment. To analyze and evaluate our scheme, we propose a probabilistic model that considers two types of events that affect routing performance for a given node: mobility and uncooperative behavior. Based on this mathematical model, we compared the performance of our proposed routing scheme with two other multipath routing protocols namely, SMORT and DMRP. Our performance results show that our scheme is highly scalable, more efficient, and resilient compared with previous related works and is particularly suitable for insecure large and dense IoT networks.

Performance Sensitivity to the High-Order Statistics of Time Interval Variables in Cellular Networks

Cell dwell time (DT) and unencumbered interruption time (IT) are fundamental time interval variables in the teletraffic analysis for the performance evaluation of mobile cellular networks. Although a diverse set of general distributions has been proposed to model these time interval variables, the effect of their moments higher than the expected value on system performance has not been reported in the literature. In this paper, sensitivity of teletraffic performance metrics of mobile cellular networks to the first three standardized moments of both DT and IT is investigated in a comprehensive manner. Mathematical analysis is developed considering that both DT and IT are phase-type distributed random variables. This work includes substantial numerical results for quantifying the dependence of system level performance metrics to the values of the first three standardized moments of both DT and IT. For instance, for a high mobility scenario where DT is modeled by a hyper-Erlang distribution, we found that call forced termination probability decreases around 60% as the coefficient of variation (CoV) and skewness of DT simultaneously change from 1 to 20 and from 60 to 2, respectively. Also, numerical results confirm that as link unreliability increases the forced termination probability increases while both new call blocking and handoff failure probabilities decrease. Numerical results also indicate that for low values of skewness, performance metrics are highly sensitive to changes in the CoV of either the IT or DT. In general, it is observed that system performance is more sensitive to the statistics of the IT than to those of the DT. Such understanding of teletraffic engineering issues is vital for planning, designing, dimensioning, and optimizing mobile cellular networks.

Energy Efficiency in Multihop Wireless Networks with Unreliable Links

Due to the increasing number of wireless devices, the issue of energy efficiency that requires high data rate with reliability has spawned tremendous research interests in recent years. In wireless networks, major problem that needs to be addressed is that multihop transmission, though requiring lower transmit power, incurs more circuit energy consumption than that of single-hop transmission and leads to more bit errors. Thus we are motivated to study the energy efficiency of multihop wireless networks with unreliable links, where such a problem is even more serious. Specifically, with a flat Rayleigh fading channel, our network model jointly considers the transmit energy and circuit energy, and characterizes the unreliability caused by the wireless nature with the assumption of probabilistic links. Based on that, we formulate our problems of energy consumption normalized by the source-destination (S-D) path loss, and derive the optimal set of signal-to-noise ratios in each hop to minimize the normalized energy consumption. In addition, our theoretical results exhibit a clear relation between the normalized energy consumption and the delay constraint, and meanwhile disclose the crucial impact that the circuit energy has on the monotonicity of the normalized energy consumption. More specifically, we find that the normalized total energy consumption with the delay constraint decreases as the number of hops increases when the number of hops is small, and increases as the number of hops increases when it is large. Extensive simulations confirm the theoretical results. Our findings shed light on the design, implementation, and operation of real-world energy-efficient multihop wireless networks.

A Coalitional Graph Game Approach for Minimum Transmission Broadcast in IoT Networks

In this work, we consider the broadcast mechanisms for both reliable links and unreliable links in the Internet of Things (IoT) networks. Focusing on the minimum transmission broadcast (MTB) problem, we propose an efficient algorithm, termed as the Connected Dominating Set Algorithm based on Coalitional Graph Game (CDSA-CGG), to find the minimum connected dominating set (MCDS). Distinct from related work in the literature which adopts a non-cooperative game approach and assumes the interaction among nodes is limited to neighboring nodes, we formulate the interaction and cooperation among nodes over reliable links and over unreliable links as a connected forwarding graph based on coalitional graph game. We prove that the forwarding graph constructed by CDSA-CGG is a Nash network. In addition, we also prove that the final resulting graph is pairwise stable. The simulation results show that the proposed coalition graph game-based algorithm performs well in terms of the number of transmissions, convergence rate, and lifetime of nodes.

On Multiple-Access in Queue-Length Sensitive Systems

We consider transmission of packets over queue-length sensitive unreliable links, where packets are randomly corrupted through a noisy channel whose transition probabilities are modulated by the queue-length. The goal is to characterize the capacity of this channel. We particularly consider multipleaccess systems, where transmitters dispatch encoded symbols over a system that is a superposition of continuous-time GIk/GI/1 queues. A server receives and processes symbols in order of arrivals with queuelength dependent noise. We first determine the capacity of single-user queue-length dependent channels. Further, we characterize the best and worst dispatch processes for GI/M/1 queues and the best and worst service processes for M/GI/1 queues. Then, the multiple-access channel capacity is obtained using point processes. When the number of transmitters is large and each arrival process is sparse, the superposition of arrivals approaches a Poisson point process. In characterizing the Poisson approximation, we show that the capacity of the multiple-access system converges to that of a single-user M/GI/1 queue-length dependent system, and an upper bound on the convergence rate is obtained. This implies that the best and worst server behaviors of single-user M/GI/1 queues are preserved in the sparse multiple-access case.

Are frequent users of social network sites good information evaluators? An investigation of adolescents’ sourcing abilities (¿Son los usuarios frecuentes de las redes sociales evaluadores competentes? Un estudio de las habilidades de los adolescentes para identificar, evaluar y hacer uso de las fuentes)

ABSTRACTThis study investigates the relationship between teenagers’ use of social networking sites (SNS) and their sourcing abilities. Sourcing is defined as students’ ability (1) to discriminate reliable and unreliable links based on source characteristics, (2) to value source criteria as means to select information resources and (3) to select reliable texts based on source characteristics. One hundred and forty-six students (M age = 14.7 years old) completed three sourcing tasks, a questionnaire on SNS use, as well as language and memory skills tests. We found that SNS frequency of use negatively predicted both participants’ ability to select the most reliable source among two conflicting sources on the same topic and their ability to cite source features when justifying their choice. SNS frequency of use was unrelated to students’ assessment of source criteria, but vocabulary level was positively related to performance in this task. We discuss various explanations for the observed relationship between teenagers’ SNS communication and their critical appraisal of information sources, and we propose avenues for instructional interventions aimed at fostering information skills.

Data Reconstructing Algorithm in Unreliable Links Based on Matrix Completion for Heterogeneous Wireless Sensor Networks

In heterogeneous wireless sensor networks, the data collection method based on compressed sensing technology is susceptible to packet loss and noise, which leads to a decrease in data reconstruction accuracy in unreliable links. Combining compressed sensing and matrix completion, we propose a clustering optimization algorithm based on structured noise matrix completion, in which the cluster head transmits the compressed sampling data and compression strategy to the base station. The algorithm we proposed can reduce the energy consumption of the node in the process of data collection, redundant data and transmission delay. The rank-1 matrix completion algorithm constructs an extremely sparse observation matrix, which is adopted by the sink node to complete the reconstruction of the whole network data. Simulation experiments show that the proposed algorithm reduces network transmission data, balances node energy consumption, improves data transmission efficiency and reconstruction accuracy, and extends the network life cycle.

On Secure Communication in Sensor Networks Under q-Composite Key Predistribution With Unreliable Links

Many applications of wireless sensor networks (WSNs) require deploying sensors in hostile environments, where an adversary may eavesdrop communications. To secure communications in WSNs, the q-composite key predistribution scheme has been proposed in the literature. In this paper, we investigate secure k-connectivity in WSNs operating under the q-composite scheme, in consideration of the unreliability of wireless links. Secure k-connectivity ensures that any two sensors can find a path in between for secure communication, even when k - 1 sensors fail. We present conditions on how to set the network parameters such that the network has secure k-connectivity asymptotically almost surely. The result is given in the form of a sharp zero-one law.

Optimal Number of Message Transmissions forProbabilistic Guarantee of Latency in the IoT.

The Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its ability to meet three Key Performance Indicators (KPIs), namely a maximum acceptable end-to-end latency L, a targeted end-to-end reliability R and a minimum network lifetime T. The IoT network has to guarantee that at least of messages generated by sensor nodes are delivered to the sink with a latency ≤L, whereas the network lifetime is at least equal to T. In this paper, we show how to provide the targeted end-to-end reliability R by means of retransmissions to cope with the unreliability of wireless links. We present two methods to compute the maximum number of transmissions per message required to achieve R. is very easy to compute, whereas minimizes the total number of transmissions necessary for a message to reach the sink. and are then integrated into a TSCH network with a load-based scheduler to evaluate the three KPIs on a generic data-gathering application. We first consider a toy example with eight nodes where the maximum number of transmissions is tuned per link and per flow. Finally, a network of 50 nodes, representative of real network deployments, is evaluated assuming is fixed. For both TSCH networks, we show that provides a better reliability and a longer lifetime than , which provides a shorter average end-to-end latency. provides more predictable end-to-end performances than Kausa, a KPI-aware, state-of-the-art scheduler.

Efficient topology control for time-varying spacecraft networks with unreliable links

In spacecraft networks, the time-varying topology, intermittent connectivity, and unreliable links make management of the network challenging. Previous works mainly focus on information propagation or routing. However, with a large number of nodes in the future spacecraft networks, it is very crucial regarding how to make efficient network topology controls. In this article, we investigate the topology control problem in spacecraft networks where the time-varying topology can be predicted. We first develop a model that formalizes the time-varying spacecraft network topologies as a directed space–time graph. Compared with most existing static graph models, this model includes both temporal and spatial topology information. To capture the characteristics of practical network, links in our space–time graph model are weighted by cost, efficiency, and unreliability. The purpose of our topology control is to construct a sparse (low total cost) structure from the original topology such that (1) the topology is still connected over space–time graph; (2) the cost efficiency ratio of the topology is minimized; and (3) the unreliability parameter is lower than the required bound. We prove that such an optimization problem is NP-hard. Then, we provide five heuristic algorithms, which can significantly maintain low topology cost efficiency ratio while achieving high reliable connectivity. Finally, simulations have been conducted on random space networks and hybrid low earth orbit/geostationary earth orbit satellite-based sensor network. Simulation results demonstrate the efficiency of our model and topology control algorithms.

On simple back-off in unreliable radio networks

In this paper, we study local and global broadcast in the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Existing work proved that efficient solutions to these problems are impossible in the dual graph model under standard assumptions. In real networks, however, simple back-off strategies tend to perform well for solving these basic communication tasks. We address this apparent paradox by introducing a new set of constraints to the dual graph model that better generalize the slow/fast fading behavior common in real networks. We prove that in the context of these new constraints, simple back-off strategies now provide efficient solutions to local and global broadcast in the dual graph model. We also precisely characterize how this efficiency degrades as the new constraints are reduced down to non-existent, and prove new lower bounds that establish this degradation as near optimal for a large class of natural algorithms. We conclude with an analysis of a more general model where we propose an enhanced back-off algorithm. These results provide theoretical foundations for the practical observation that simple back-off algorithms tend to work well even amid the complicated link dynamics of real radio networks.

A Quantitative Measure of Reliability for Wireless Sensor Networks

The reliability of a wireless sensor network is often associated with its capacity to maintain an end-to-end connection in the presence of unreliable links or node failure. It is also associated with the level of partitioning the network suffers when some nodes fail or exhaust their batteries. Despite being a critical feature, often it is not clear how it can be expressed in quantifiable terms. We assert that Katz's status index can be used as an adequate measure of reliability. Originally proposed for sociometric analysis, it assigns a value of significance to each node in a network. Some of the underlying assumptions made and the intermediate steps taken to construct the status index are not applicable for our case, but we shall demonstrate that their effect on the final result is marginal.

A Multi-Layer Self-Healing Algorithm for WSNs

The implementation of Wireless Sensor Networks (WSNs) is a challenging task due to their intrinsic characteristics, e.g., energy limitations and unreliable wireless links. Considering this, we have developed the Disjoint path And Clustering Algorithm (DACA) that combines topology control and self-healing mechanisms to increase the network lifetime with minimum loss of coverage. Initially, DACA constructs a tree that includes all nodes of the network by using the Collection Tree Protocol (CTP). This tree is an initial communication backbone through which DACA centralizes the information. Then, DACA builds a set of spatial clusters using Kmeans and selects the Cluster Heads (CHs) using Particle Swarm Optimization (PSO) and a multi-objective optimization (MOO) function. Subsequently, DACA reconstructs the tree using only the CHs. In this way, DACA reduces the number of active nodes in the network and saves energy. Finally, DACA finds disjoint paths on the reconstructed tree by executing the N-to-1 multipath discovery protocol. By doing so, the network can overcome communications failures with a low control message overhead. The simulations on Castalia show that DACA considerably extends the network lifetime by having a set of inactive nodes and disjoint paths that support the communication when active nodes die. Besides, DACA still maintains a good coverage of the area of interest despite the inactive nodes. Additionally, we evaluate the shape of the tree (i.e., the average number of hops) and the risk of connection loss of the network.

Optimal and suboptimal channel precoding and decoding matrices for linear video coding

Linear video coding (LVC) has recently emerged as a very promising paradigm for robust video delivery over unreliable channels. The pioneering LVC paper, introducing SoftCast, showed that, a cross-layer approach, based on linear-only processing followed by analog modulation, was able to improve the quality of received video with respect to traditional, layered approaches, when unreliable links to several users are considered. This paper considers the power allocation problem when the transmission channel consists of several sub-channels, each with its own power constraint. This framework models, e.g., multi-antenna, DSL, or powerline transmission systems. Minimizing the mean-square error at a receiver leads to an precoding and decoding matrix design problem. Our contributions consist in (1) formulating the matrix design problem in such a way that a multi-level water-filling solution proposed for MIMO channels can be adapted to LVC; (2) the proposal of three suboptimal power allocations techniques, with different trade-offs between complexity and efficiency; (3) a precoding matrix design for the multiple receivers scenario; (4) extensive simulations of the power allocation methods. The proposed optimal power allocation largely outperforms a simple adaptation of the allocation considered in SoftCast for the per-subchannel power constrained problem; moreover two of the suboptimal solutions perform very close to the optimal one, with a sensibly reduced complexity.

Fuzzy Output Tracking Control and Filtering for Nonlinear Discrete-Time Descriptor Systems Under Unreliable Communication Links.

In this paper, the problems of output tracking control and filtering are investigated for Takagi-Sugeno fuzzy-approximation-based nonlinear descriptor systems in the discrete-time domain. Especially, the unreliability of the communication links between the sensor and actuator/filter is taken into account, and the phenomenon of packet dropouts is characterized by a binary Markov chain with uncertain transition probabilities, which may reflect the reality more accurately than the existing description processes. A novel bounded real lemma (BRL), which ensures the stochastic admissibility with H∞ performance for fuzzy discrete-time descriptor systems despite the uncertain Markov packet dropouts, is presented based on a fuzzy basis-dependent Lyapunov function. By resorting to the dual conditions of the obtained BRL, a solution for the designed fuzzy output tracking controller is given. A design method for the full-order fuzzy filter is also provided. Finally, two examples are finally adopted to show the applicability of the achieved design strategies.

A kind of novel RSAR protocol for mobile vehicular Ad hoc network

MVANET (Mobile Vehicular Ad hoc Network) as one part of Mobile Vehicular Ad hoc Network (MANET) has the feature: unreliable communication link and frequent change of network topology. In order to improve the communication link reliability and efficient routing, a kind of novel RSAR (rewarding smart Ad hoc routing) protocol for Mobile Vehicular Ad hoc Network is presented in this paper. Based on our suggested model, the reliability of the communication link is assessed and design a novel routing protocol according to the strategy of deep learning. As a kind of machine learning approach, the D-Learning (Deep-Learning) algorithm can be helpful to get the reliable routing path. The advantage of the RSAR protocol is evaluated by the simulator and tests of the practical applications. The experimental results show that RSAR exhibits good results at a delivery rate, end-to-end delay and average hops compared with SLBF, QLAODV and GPSR.

$k$ -Connectivity of Inhomogeneous Random Key Graphs With Unreliable Links

We consider secure and reliable connectivity in wireless sensor networks that utilize the heterogeneous random key predistribution scheme. We model the unreliability of wireless links by an on/off channel model that induces an Erdős-Renyi graph, while the heterogeneous scheme induces an inhomogeneous random key graph. The overall network can thus be modeled by the intersection of both graphs. We present conditions (in the form of zero-one laws) on how to scale the parameters of the intersection model, so that with high probability: i) all of its nodes are connected to at least ${k}$ other nodes, i.e., the minimum node degree of the graph is no less than $ {k}$ , and ii) the graph is $ {k}$ -connected, i.e., the graph remains connected even if any $ {k} - {1}$ nodes leave the network. These results are shown to complement and generalize several previous results in the literature. We also present numerical results to support our findings in the finite-node regime. Finally, we demonstrate via simulations that our results are also useful when the on/off channel model is replaced with the more realistic disk communication model .

Integrating power assignment into energy‐efficient routing in E2E retransmission systems

Routing design is an effective mechanism to improve the energy-efficiency in packet transmissions for wireless multihop networks. Meanwhile, the total energy consumption for packet transmissions over a path comprising of several unreliable links depends on the power assignment on each link. In this study, the authors address the energy-efficient routing, which integrates with the optimal power assignment, in end-to-end (E2E) retransmission systems. The process of packet transmission across a path in E2E systems is modelled as a random walk. The expected energy consumed for the packet transmission is then calculated. As the expected energy consumption closely relies on the transmit power assigned on the path, it is necessary to integrate the power assignment into the energy-efficient routing. The optimal power assignment on the candidate path is analytically derived for minimising the expected energy consumption. Specially, the energy-efficient routing integrated with power sssignment (EERPA) algorithm is developed to find the optimal path among all candidate paths with all possible power assignments. Simulations demonstrate the efficiency of the authors' EERPA algorithm.

Adaptive Transmission Control for Software Defined Vehicular Networks

Efficient transmission control is an intricate issue in vehicular networks due to the inherent topology dynamics and unreliable link conditions. Leveraging flexible management in software-defined vehicular networks, we propose a software-defined adaptive transmission control protocol (SATCP) for selecting various transmission control policies to adapt to the time-varying vehicular environment. We formulate the optimal transmission control problem, and develop a practical heuristic algorithm for adaptive transmission control. NS-3 based preliminary simulations are conducted to verify that SATCP achieves an improvement by 27.8% than TcpHtcp, and by 54.4% than TcpVegas in terms of average network throughput.

Delay-constrained flooding in extremely low-duty-cycle sensor networks

Flooding is a fundamental function for the network-wide dissemination of command, query, and code update in wireless sensor networks. However, it is challenging to enable fast and energy-efficient flooding in sensor networks with low-duty cycles because it is rare that multiple neighboring nodes wake up at the same time, making broadcast instinct of wireless radio unavailable. The unreliability of wireless links deteriorates the situation. In this work, we study the delay-constrained flooding problem in order to disseminate data packets to all nodes within given expected delivery delay. In particular, a transmission power control–based flooding algorithm is proposed to reduce the flooding delay in such low-duty-cycle sensor networks. According to the soft delay bound, each node can locally adjust its transmission power level. To alleviate transmission conflicts, the backoff method with transmission power adaptive mechanism has been proposed. Based on the large-scale simulations, we validate that our design can reduce flooding delay with small extra energy expenditure compared with conventional flooding schemes.