Unreliable Wireless Links Research Articles

A comprehensive survey onQoSfor video transmission in heterogeneous mobile ad hoc network

AbstractMajor challenging issue in H‐MANETs (Heterogeneous Mobile Ad hoc Networks) is video transmission because it gets affected due to various factors like dynamic change in topology, interference, node mobility, collusion, and so on. Periodic connection is caused by the topology dynamic change, which leads to significant packet loss. Advancements provide the technical basis for video streaming over H‐MANETs in wireless networking and mobile devices. And efforts to achieve video transmission via H‐MANETs have run into some barriers, which have been overcome in various ways. Nonetheless, H‐MANETs are essential to provide video transmission certainty and quality provisioning. Due to the limited resources, the unreliability of wireless links, node mobility, and heterogeneity, establishing video streaming or enabling real‐time multimedia applications over H‐MANET with acceptable QoS (quality of service) poses several issues. The article's main goal is to survey QoS‐based video transmission in H‐MANETs. This study discusses the video transmission method in H‐MANET and the importance of the QoS that may be used for video transmission in H‐MANET. Various routing protocols and existing methodologies to improve QoS for video transmission in H‐MANET are discussed. In addition, the impact of delay in video transmission over H‐MANET has been discussed. Several obstacles and issues have been highlighted in providing QoS for video transmission in H‐MANET. From 2013 to 2021, a systematic literature review (SLR) is done for QoS‐based video transmission in the H‐MANET. This survey systematically gives the technical direction for research on QoS‐based video transmission and discusses potential future aspects.

RSock: A resilient routing protocol for mobile Fog/Edge networks

Fog/Edge networks (FENs) refer to wireless networks in which a “close-to-end-user cloud” is established amongst handheld devices to offer communication, computation, and storage services. In this paper, we focus on FENs that are formed by on-body devices of first responders and leveraged (as mission-critical deployable networks) in disaster-response scenarios. Designing an efficient routing protocol for such FENs is challenging since they exhibit dynamic connectivity characteristics and unreliable wireless links due to the mobility of devices, wireless obstacles, etc. Moreover, FENs applications in disaster-response scenarios distribute their processing/storage tasks to local nodes and accordingly have diverse requirements in terms of packet delivery’s rate and delay (PDR and PDD). On the other hand, most of the state-of-the-art routing protocols are not suitable for FENs since their target networks have static connectivity characteristics. Furthermore, these protocols provide poor support for seamless mobility communication and for exploiting all devices’ wireless interfaces as well as their initial/subsequent deployment(s) require pushing changes to the TCP/IP stack. In this paper, we present Resilient Socket (RSock), a limited-replication-based routing protocol that decides whether to use packet replication and by how much based on the mission-critical deployable FENs connectivity conditions. RSock is an identity-based routing protocol that exploits all wireless interfaces to route/deliver packets for IP-address/interface agnostic applications. We design RSock as an easy-to deploy-and-evolve protocol and we demonstrate its feasibility through a reliable full-system implementation for Linux and Android platforms . Real-world experiments show that RSock performs well in disaster-response scenarios.

A Novel Approach for Enhancing the Network Life Time of Secure ML_RPL Routing Protocol in Internet of Things by Using PROB_ATT_SCHEME

Abstract-- IoT devices are having self-configuration in nature for establishing adhoc networks to monitor physical activities like environmental sensing, Intelligent Traffic Management Systems (ITMS) and so on even in unmanned areas. Benefits of these networks are numerous and few of them are no infrastructure and deploying spontaneously, cost effective set up of temporary and dynamic networks and so on. Moreover, characteristics like unreliable wireless links, resource constraints related to energy and power and dynamic topology, makes the protocols that are developed recently to ignore the security needs with the intention of satisfying quality of service (QoS). IoT makes the jobs easier and smarter, but still security mechanisms are challenging for resource constrained devices like denial of service attacks (Stuxnet), blackhole attacks are the examples of attacks which maliciously controls these devices causing damage. Remote Attestation (RA) is one tool which efficiently identifies a malicious entity in the network. However, the proposed tool not suitable for large size mobile IoT networks, where nodes are connected in heterogeneous manner with resource constraints for the nodes. It is understood that it is necessary to do the necessary research for extending the network life time of resources constraint nodes existing in the network along with secure connection between nodes of the network, In present work, proposed a probability-based attestation scheme (PROB_ATT) for improving routing and security in IoT network. With the help of the estimated probability value of network path, attestation value is included in the network along with data. With application of trickle time, attestation is verified and data transmission is performed. After estimation of probability within network data transmission is performed based on trust mechanism. Simulation analysis stated that PROB_ATTT scheme reduces energy consumption, packet loss ratio and delay as 20%, 10% and 5% respectively when compared with Machine Learning based RPL protocol. Whereas the other important performance metrics: energy efficiency, throughput and Packet delivery rate performance is improved around 20% than ML based RPL protocol. Keywords-- Attestation scheme, Probability attestation scheme (PROB_ATT), Security, Trust Mechanism, Trickle Timer, MAC layer,RPL,ML_RPL protocol

Collision Avoidance Geographic P2P-RPL in Multi-Hop Indoor Wireless Networks

In home and building automation applications, wireless sensor devices need to be connected via unreliable wireless links within a few hundred milliseconds. Routing protocols in Low-power and Lossy Networks (LLNs) need to support reliable data transmission with an energy-efficient manner and short routing convergence time. IETF standardized the Point-to-Point RPL (P2P-RPL) routing protocol, in which P2P-RPL propagates the route discovery messages over the whole network. This leads to significant routing control packet overhead and a large amount of energy consumption. P2P-RPL uses the trickle algorithm to control the transmission rate of routing control packets. The non-deterministic message suppression nature of the trickle algorithm may generate a sub-optimal routing path. The listen-only period of the trickle algorithm may lead to a long network convergence time. In this paper, we propose Collision Avoidance Geographic P2P-RPL, which achieves energy-efficient P2P data delivery with a fast routing request procedure. The proposed algorithm uses the location information to limit the network search space for the desired route discovery to a smaller location-constrained forwarding zone. The Collision Avoidance Geographic P2P-RPL also dynamically selects the listen-only period of the trickle timer algorithm based on the transmission priority related to geographic position information. The location information of each node is obtained from the Impulse-Response Ultra-WideBand (IR-UWB)-based cooperative multi-hop self localization algorithm. We implement Collision Avoidance Geographic P2P-RPL on Contiki OS, an open-source operating system for LLNs and the Internet of Things. The performance results show that the Collision Avoidance Geographic P2P-RPL reduced the routing control packet overheads, energy consumption, and network convergence time significantly. The cooperative multi-hop self localization algorithm improved the practical implementation characteristics of the P2P-RPL protocol in real world environments. The collision avoidance algorithm using the dynamic trickle timer increased the operation efficiency of the P2P-RPL under various wireless channel conditions with a location-constrained routing space.

Adaptive Forwarding With Probabilistic Delay Guarantee in Low-Duty-Cycle WSNs

Despite many existing research on data forwarding in low-duty-cycle wireless sensor networks (WSNs), relatively little work has been done on energy-efficient data forwarding with probabilistic delay bounds. Probabilistic delay guarantees ( i.e. , delay bounded data delivery with reliability constraints) are of increasing importance for many delay-constrained applications, since deterministic delay bounds are prohibitively expensive to guarantee in WSNs. However, radio duty-cycling and unreliable wireless links pose challenges for achieving the probabilistic delay guarantee in WSNs. In this paper, we propose EEAF, a novel energy-efficient adaptive forwarding technique tailored for low-duty-cycle WSNs with unreliable wireless links. We show the existence of path diversity in low-duty-cycle WSNs, where delay-optimal routing and energy-optimal routing are likely following different paths. The key idea of EEAF is to exploit the intrinsic path diversity to provide probabilistic delay guarantees while minimizing transmission cost. In EEAF, an early arriving packet will be adaptively switched to the energy-optimal path for energy conservation. Delay quantiles are derived at each node in a distributed manner and are used as the guidelines in the adaptive forwarding decision making. Extensive testbed experiment and large-scale simulation show that EEAF effectively reduces the transmission cost by 12%~25% with probabilistic delay guarantees under various network settings. In addition, we extend the EEAF technique with data aggregation for event-based traffic scenarios. Evaluation using publicly available WSN event traffic traces yields very encouraging results with up to 40% energy saving in probabilistic delay bounded data delivery.

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.

Low Overhead Localized Routing in Mobile Ad Hoc Networks

Mobile Opportunistic Networks (OppNets) are infrastructure-less networks consisting of wireless mobile nodes and have been a focus of research for years. OppNets can be scaled up to support rapid growth of wireless devices and technologies, especially smartphones and tablets. Mobile Ad Hoc Networks (MANETs), one of OppNets technologies, have a high potential to be used for facilitating an extension for the Internet and a backup communication platform in disaster situation. However, a connection disruption due to node mobility and unreliable wireless links is possible to trigger a flooding operation of route repair process. This results in transmission delay and packet loss. The flooding of routing packets is an expensive operation cost in MANETs which affects network reliability and wastes limited resources such as network bandwidth and node energy. These are obstacles to practical implementation of MANETs in real-world environment. In this paper, we propose Low Overhead Localized Flooding (LOLF), an efficient overhead reduction routing extension based on Query Localization (QL) routing protocol. The purpose of this work is to control the propagation of routing packets in the route discovery and route repair mechanisms while incurring only a small increase in the size of control information in the packet. Simulation results from extensive experiments show that our proposed method can reduce overall routing overhead, energy consumption, and end-to-end delay without sacrificing the packet delivery ratio compared to existing protocols.

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.

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.

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.

LCD: Light‐weight control model for data plane in software‐defined wireless sensor networks

AbstractWith the introduction of software‐defined networking (SDN) into wireless sensor networks (WSNs) to simplify network management and increase agility, software‐defined WSNs (SDWSNs) came into being. Since SDN adopts an idea of centralized control, reliable control is a necessary guarantee of its performance. However, in SDWSN, the unreliable wireless links pose a significant challenge to the reliable control of data plane. In view of this, this paper adopts the idea of separating the forwarding process of control flow and data flow and presents a light‐weight control model for data plane in SDWSN. Based on the network global view, the model constructs an independent control forwarding layer to route control flow. The light‐weight feature of this model lies in that there is no need to deploy additional control networks. Finally, we design a fast update algorithm for the control failure that may occur by searching for the replacement of neighboring control nodes and achieve efficient maintenance of the control forwarding layer. The simulation results show that the proposed model has shorter request‐response time than the original SDN‐WISE, and the impact on data plane forwarding performance is also within the acceptable range.

A Kernel-Based Compressive Sensing Approach for Mobile Data Gathering in Wireless Sensor Network Systems

The recent advances of compressive sensing (CS) have witnessed a great potential of efficient compressive data gathering (CDG) in wireless sensor network systems (WSNSs). However, most existing work on CDG mainly focuses on multihop relaying strategies to improve the performance of data gathering. In this paper, we propose a mobile CDG scheme including a random walk-based algorithm and a kernel-based method for sparsifying sensory data from irregular deployments. The proposed scheme allows a mobile collector to harvest data by sequentially visiting a number of nodes along a random path. More importantly, toward building the gap between CS and machine learning theories, we explore a theoretical foundation for understanding the feasibility of the proposed scheme. We prove that the CS matrices, constructed from the proposed random walk algorithm combined with a kernel-based sparsity basis, satisfy the restricted isometry property. Particularly, we also show that m = O(klog(n/k)) measurements collected by a mobile collector are sufficient to recover a k-sparse signal and t = O(klog(n/k)) steps are required to collect these measurements in a network with n nodes. Finally, we also present extensive numerical results to validate the effectiveness of the proposed scheme by evaluating the performance in terms of energy consumption and the impact of packet losses. The numerical results demonstrate that the proposed scheme is able to not only significantly reduce communication cost but also combat unreliable wireless links under various packet losses compared to the stateof-the-art schemes, which provides an efficient alternative to data relaying approaches for CDG in WSNS.

A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs.

In wireless sensor networks (WSNs), communication links are typically error-prone and unreliable, so providing reliable and timely data routing for loss- and delay-sensitive applications in WSNs it is a challenge issue. Additionally, with specific thresholds in practical applications, the loss and delay sensitivity implies requirements for high reliability and low delay. Opportunistic Routing (OR) has been well studied in WSNs to improve reliability for error-prone and unreliable wireless communication links where the transmission power is assumed to be identical in the whole network. In this paper, a Cross-layer Optimized Opportunistic Routing (COOR) scheme is proposed to improve the communication link reliability and reduce delay for loss-and-delay sensitive WSNs. The main contribution of the COOR scheme is making full use of the remaining energy in networks to increase the transmission power of most nodes, which will provide a higher communication reliability or further transmission distance. Two optimization strategies referred to as COOR(R) and COOR(P) of the COOR scheme are proposed to improve network performance. In the case of increasing the transmission power, the COOR(R) strategy chooses a node that has a higher communication reliability with same distance in comparison to the traditional opportunistic routing when selecting the next hop candidate node. Since the reliability of data transmission is improved, the delay of the data reaching the sink is reduced by shortening the time of communication between candidate nodes. On the other hand, the COOR(P) strategy prefers a node that has the same communication reliability with longer distance. As a result, network performance can be improved for the following reasons: (a) the delay is reduced as fewer hops are needed while the packet reaches the sink in longer transmission distance circumstances; (b) the reliability can be improved since it is the product of the reliability of every hop of the routing path, and the count is reduced while the reliability of each hop is the same as the traditional method. After analyzing the energy consumption of the network in detail, the value of optimized transmission power in different areas is given. On the basis of a large number of experimental and theoretical analyses, the results show that the COOR scheme will increase communication reliability by 36.62–87.77%, decrease delay by 21.09–52.48%, and balance the energy consumption of 86.97% of the nodes in the WSNs.

Towards minimum-delay and energy-efficient flooding in low-duty-cycle wireless sensor networks

Wireless sensor networks (WSNs) play a very important role in realizing Internet of Things (IoT). In many WSN applications, flooding is a fundamental network service for remote network configuration, diagnosis or disseminating code updates. Despite a plethora of research on flooding problem in the literature, there has been very limited research on flooding tree construction in asynchronous low-duty-cycle WSNs. In this paper, we focus our investigation on minimum-delay and energy-efficient flooding tree construction considering the duty-cycle operation and unreliable wireless links. We show the existence of the latency-energy trade-off in flooding. We formulate the problem as a undetermined-delay-constrained minimum spanning tree (UDC-MST) problem, where the delay constraint is known a posteriori. Due to the NP-completeness of the UDC-MST problem, we design a distributed Minimum-Delay Energy-efficient flooding Tree (MDET) algorithm to construct an energy optimal tree with flooding delay bounding. Through extensive simulations, we demonstrate that MDET achieves a comparable delivery latency with the minimum-delay flooding, and incurs only 10% more transmission cost than the lower bound, which yields a good balance between flooding delay and energy efficiency.

Geographic Segmented Opportunistic Routing in Cognitive Radio Ad Hoc Networks Using Network Coding

In cognitive radio ad hoc networks (CRAHNs), the secondary users’ links are interrupted by the arrival of primary users, which leads to a significant increase of the number of transmissions per packet. Since network coding and opportunistic routing can reduce the number of transmissions over unreliable wireless links, they are more suitable for CRAHNs. Network coding-based opportunistic routing has been well studied in previous works for traditional ad hoc networks. However, existing approaches have limitations to handle CRAHNs. First, the routing decisions of these methods aim to find one optimal forwarding set for the whole path from the source to the destination. If the channel conditions change dynamically, the pre-selected forwarding set may become unavailable or non-optimal. Second, their coding schemes are not efficient enough to cope with the dynamic spectrum variation in CRAHNs. In this paper, we attempt to overcome these limitations and propose a network-coding-based geographic segmented opportunistic routing scheme for CRAHNs, by fully embracing its characteristics. In our scheme, the whole path from the source to the destination is cut down into several smaller opportunistic route segments, where the packets are transmitted through multiple segments based on a step-by-step forwarding procedure until all the packets are delivered to the destination. Since our scheme utilizes only local spectrum opportunities, topology information, and geometric conditions to compute the forwarding set for each short-term opportunistic route segment, it can better adapt to dynamic spectrum environments and changing network topologies in CRAHNs. Furthermore, we construct a coding graph to show that our coding problem is a reduction from the maximum clique problem, and we propose an efficient network coding strategy to solve it. Simulation results show that our scheme can achieve a considerable performance, compared with the latest opportunistic routing protocols designed for CRAHNs.

Low Complexity Parity Check Code for Futuristic Wireless Networks Applications

The Internet of Things refers to the aptitude of remotely connecting and monitoring anything, anytime, and anywhere via futuristic wireless networks. Due to the unreliable wireless links, broadcast nature of wireless transmissions, interference and noisy transmission channels, frequent topology changes, and the various quality of wireless channel, there are challenges in providing high data rate service, high throughput, high packet delivery ratio, low end-to-end delay, and reliable services. In wireless network and real time application systems, low complexity and shorter codeword length in channel coding scheme are preferred. Consequently, in order to address these challenges, we propose a novel error detection and correction codes called the low-complexity parity-check (LCPC) codes with short codeword lengths for futuristic wireless networks applications. The proposed codes have less complexity and lower memory requirement in comparison to turbo and low-density parity-check (LDPC) codes. Simulation results demonstrated that the proposed LCPC codes outperform the Hamming and Reed–Solomon codes, in addition to the renowned LDPC codes. It offers up to 3-dB coding gain.

An optimized intrusion response system for MANET:

Mobile Ad-Hoc NETworks (MANETs) are highly vulnerable to various security threats due to the numerous constraints they present, such as the absence of a fixed infrastructure, the dynamic topology change, their dependence on cooperative communication, the limited resource constraints, the unreliability of wireless links, and most importantly the lack of a clear line of defence. In this paper, MANET security issues are addressed through a comprehensive analysis of some common security threats, mainly blackhole, grayhole and the selfish behaviour attack. This has led to the building of a new intrusion response system denoted MASID-R-SA. This system is capable of providing autonomic systematic responses based on the intrusions’ measured severity level. The main objective of this approach is to better survive both single and multiple intrusion scenarios while minimizing the negative consequences of adopting typical static responses. We demonstrate through simulations the effectiveness of the proposed intrusion response system in appropriately responding to both single and multiple intrusions. For instance, a true detection rate of 97,23% and an average of 96,33% response success rate are achieved. The study revealed, also, that the proposed system solves some critical issues related to network partitioning and remerging efficiently.

An Energy-Aware Hybrid ARQ Scheme with Multi-ACKs for Data Sensing Wireless Sensor Networks.

Wireless sensor networks (WSNs) are one of the important supporting technologies of edge computing. In WSNs, reliable communications are essential for most applications due to the unreliability of wireless links. In addition, network lifetime is also an important performance metric and needs to be considered in many WSN studies. In the paper, an energy-aware hybrid Automatic Repeat-reQuest protocol (ARQ) scheme is proposed to ensure energy efficiency under the guarantee of network transmission reliability. In the scheme, the source node sends data packets continuously with the correct window size and it does not need to wait for the acknowledgement (ACK) confirmation for each data packet. When the destination receives K data packets, it will return multiple copies of one ACK for confirmation to avoid ACK packet loss. The energy consumption of each node in flat circle network applying the proposed scheme is statistical analyzed and the cases under which it is more energy efficiency than the original scheme is discussed. Moreover, how to select parameters of the scheme is addressed to extend the network lifetime under the constraint of the network reliability. In addition, the energy efficiency of the proposed schemes is evaluated. Simulation results are presented to demonstrate that a node energy consumption reduction could be gained and the network lifetime is prolonged.

Link quality aware channel allocation for multichannel body sensor networks

Body Sensor Network (BSN) is a typical Internet-of-Things (IoT) application for personalized health care. It consists of economically powered, wireless and implanted medical monitoring sensor nodes, which are designed to continually collect the medical information of the target patients. Multichannel is often used in BSNs to reduce the spectrum competition of the tremendous sensor nodes and the problem of channel assignment has attracted much research attention. The health sensing data in BSNs is often required to be delivered to a sink node (or server) before a certain deadline for real time monitoring or health emergency alarm. Therefore, deadline is of significant importance for multichannel allocation and scheduling. The existing works, though designed to meet the deadline, often overlook the impact of the unreliable wireless links. As a result, the health sensing data can still be overdue because of the scheduled lossy links. Besides, potential collisions in the schedules also incur considerable delay in delivering the sensing data. In this paper, we propose a novel deadline-driven Link quality Aware Channel Assignment scheme (LACA), where link quality, deadlines and collisions are jointly considered. LACA prioritizes links with urgent deadlines and heavy collisions. Besides, LACA allows the exploitation of the spare slots for retransmissions on lossy links, which can further reduce the retransmission delay. Extensive simulation experiments show that compared to the existing approaches, LACA can better utilize the wireless spectrum and achieve higher packet delivery ratio before the deadline.

Wireless Network Inference and Optimization: Algorithm Design and Implementation

This paper addresses the problem of joint inference and optimization in wireless networks. An optimization framework based on information-geometric network inference is developed and implemented (using a real radio emulation testbed) with scalable solutions to infer the end-to-end rate distributions of stochastic network flows from link rate measurements. The proposed low-complexity solutions apply when the underlying network inference (network tomography) problem can be decomposed to smaller-size subproblems that are solved independently by partially inferring only the flow rates of interest. The solutions are extended to infer flow rates jointly with link loss rates when retransmissions are considered over unreliable wireless links. By using the inferred distributions of flow rates, an inference mechanism is presented to optimize the network performance. First, the distributions of flow rates are inferred from the average rate measurements on selected links. Then, the distributions of all links rates are computed from the inferred distributions of flow rates. Finally, these inference results are used with network optimization. The weighted sum of link outage probabilities is minimized by adapting power control or routing decisions in mobile wireless access. This approach is iterated between network inference and optimization, providing link outage and end-to-end throughput gains compared to static approaches with fixed network (inference and optimization) parameters. The joint network inference and optimization framework is implemented with real configurable radios and the performance is verified with hardware-in-the-loop emulation test results that are obtained with actual radio transmissions over emulated channels.