Feedback Packets Research Articles

SVM‐SFL based malicious UAV detection in wireless sensor networks

SummaryIn the modern era, unmanned aerial vehicle (UAV) based wireless sensor networks (WSN) are rising technologies in wireless communication. Through UAV, the sensed data can be forwarded to the base station. However, the increase in network users leads to several malicious attacks on UAVs. Hence, it affects the performance of a WSN platform while transmitting private information through UAVs. Therefore, the proposed study intends to develop an effective malicious UAV detection approach using a machine‐learning algorithm. Initially, the deployed sensor nodes in WSN are utilized to collect the environmental data. These sensor nodes transmit the collected data to the UAV. During data transmission, the sensor nodes generate a feed packet (authentication parameter) and forward it to the UAV along with the sensed information. The feedback packet is encrypted through a proxy re‐encryption scheme to secure the input data. These encrypted packets with the sensed input data are then transmitted to the base station. Finally, the feedback packet is decrypted and attains the actual input information. From the received data, the classification is performed using a proposed support vector machine with a shuffled frog leap (SVM‐SFL) approach. The proposed approach is implemented with the NS3 Python tool, and the results are analyzed by evaluating several performance matrices. Compared with other existing methods, the proposed study obtained improved results in terms of accuracy (98.61%), precision (98.5%), sensitivity (98.63%), and F‐measure (98.62%).

Event-triggered sliding mode control for networked linear systems

This paper investigates the control-based event-triggered sliding mode control for a networked linear system whose feedback information is transmitted over a digital communication network. In this paper, a novel event-triggered mechanism based on control value is proposed. Different from traditional event-triggered mechanisms that are normally based on states, our mechanism pays more attention to the desired control input value of the system. When the deviation between the current control input and the control input being calculated on the basis of the previous system state exceeds a given threshold, an event is triggered. For the sake of reducing the information to be transmitted, a quantization policy is executed and only a few bits are needed to transmit the feedback symbol of each sample. The combination of the control-based event-triggered mechanism and the quantization policy can significantly reduce both the transmission frequency and the number of bits of each feedback packet. For the concerned system, sliding mode control is implemented. The reachability of the sliding mode surface and the robust stability of the system are analyzed by fully taking quantization effects into account. Moreover, the effects of transmission delay of feedback packets on the event-triggering mechanism are considered. Under the proposed mechanism, the lower bound of event intervals is proven to be non-zero, i.e., the Zeno behavior is excluded. Simulations of a mechanical system are done to further verify the superiority of the proposed mechanism.

A TCP Acceleration Algorithm for Aerospace-Ground Service Networks

The transmission of satellite payload data is critical for services provided by aerospace ground networks. To ensure the correctness of data transmission, the TCP data transmission protocol has been used typically. However, the standard TCP congestion control algorithm is incompatible with networks with a long time delay and a large bandwidth, resulting in low throughput and resource waste. This article compares recent studies on TCP-based acceleration algorithms and proposes an acceleration algorithm based on the learning of historical characteristics, such as end-to-end delay and its variation characteristics, the arrival interval of feedback packets (ACK) at the receiving end and its variation characteristics, the degree of data packet reversal and its variation characteristics, delay and jitter caused by the security equipment's deep data inspection, and random packet loss caused by various factors. The proposed algorithm is evaluated and compared with the TCP congestion control algorithms under both laboratory and ground network conditions. Experimental results indicate that the proposed acceleration algorithm is efficient and can significantly increase throughput. Therefore, it has a promising application prospect in high-speed data transmission in aerospace-ground service networks.

Stabilizing bit rate conditions for a scalar linear event-triggered system with Markov dropouts

This paper investigates the stabilization problem of a scalar linear event-triggered system via a bit-rate-limited network, which suffers from bounded transmission delay and Markov feedback dropouts. Necessary and sufficient bit rate conditions for the asymptotic stability of the concerned system are derived in the mean square sense. Due to the influence of transmission delay and Markov dropouts, a higher bit rate is required for stabilization, which is quantitatively characterized. To overcome the difficulties induced by the temporal correlation of Markov dropouts, a variable bit rate quantization policy is proposed to achieve the minimum-bit-rate stability by appropriately determining the number of quantization bits for each feedback packet. The obtained sufficient bit rate condition is shown to be also necessary in some special cases. Simulations are done to verify the effectiveness of our results.

Event-Triggered Stabilizing Bit Rate Conditions for an n-Dimensional Linear System With i.i.d. Feedback Dropouts.

This article aims to stabilize an n -dimensional linear time-invariant (LTI) system, whose feedback packets are transmitted through a digital communication network. The digital network suffers from network delay and independent and identically distributed (i.i.d.) feedback dropouts, which may destabilize the system. The coupling among multiple state variables may further harm the stability of the system. In order to deal with these issues and save the occupied bandwidth of the feedback network, we propose a periodic event-triggering strategy. In our strategy, the state is measured periodically, but only quantized and transmitted when a certain condition is triggered. By well balancing the state coupling and making full use of both the information inside transmitted feedback packets and the one carried by sampling time instants, our strategy can maintain the desired mean square stability at a lower bit rate than conventional periodic sampling policies. The obtained stabilizing bit rate conditions are determined by the processing and network delays, the dropout rate, and the unstable eigenvalues of the system matrix, but independent of the process noise. Moreover, the lack of the direct state access does not incur any additional stabilizing bit rate. Simulations are done to confirm the effectiveness of the obtained stabilizing bit rate conditions.

A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks.

In wireless sensor networks, it is important to use the right number of sensors to optimize the network and consider the key design and cost. Due to the limited power of sensors, important issues include how to control the state of the sensor through an automatic control algorithm and how to power-save and efficiently distribute work. However, sensor nodes are usually deployed in dangerous or inaccessible locations. Therefore, it is difficult and impractical to supply power to sensors through humans. In this study, we propose a high reliability control algorithm with fast convergence and strong self-organization ability called the sensor activity control algorithm (SACA), which can efficiently control the number of sensors in the active state and extend their use time. In the next round, SACA considers the relationship between the total number of active sensors and the target value and determines the state of the sensor. The data transmission technology of random access is used between the sensor and the base station. Therefore, the sensor in the sleep state does not need to receive the feedback packet from the base station. The sensor can achieve true dormancy and power-saving effects. The experimental results show that SACA has fast convergence, strong self-organization capabilities, and power-saving advantages.

Event‐triggered stabilization of multi‐dimensional nonlinear systems under communication constraints

AbstractThis article investigates the input‐to‐state stability of a multi‐dimensional nonlinear system, which transmits feedback information through an unreliable communication network with bounded network delay and occasional dropouts. In order to stabilize the system and save the occupied communication resources, we propose a model‐based periodic event‐triggered control strategy which can make full use of feedback packets, especially the information contained in their triggering time instants. However, both the network delay and feedback dropouts will reduce the amount of information extracted from triggering/sampling time instants, and significantly degrade the system performance. To handle them, this article provides a novel encoding and decoding method to make use of the timing information and the bits inside each feedback packet for both state and output feedback cases. Compared with the conventional time‐driven strategies, the proposed event‐triggered one can stabilize the concerned nonlinear system at a lower bit rate. The effectiveness and bit rate advantage of the proposed strategy are further illustrated through simulations.

Detection of Wormhole Attack and Secure Path Selection in Wireless Sensor Network

In Wireless Sensor Network (WSN), securable data transmission is one of the most challenges. During the transmission between the source and a destination node, routing information of the particular path may be misbehaved by the particular nodes which are known as wormhole nodes/attackers. The paths which include the wormhole nodes are known as wormhole attacked paths. For improving security in WSN, these wormhole attacked paths should be identified. To achieve this, wormhole attack detection method and optimal or secure path selection are presented in this paper. Initially, ‘K’ paths or multiple paths are generated between source and destination using Ad-hoc On demand Multipath Distance Vector (AOMDV) routing protocol. Then, the source node identifies the wormhole attacked path by verifying the Detection Packet (DP) and Feedback Packet (FP) from the destination. After detecting the wormhole attacked paths, the source node selects the optimal path among the attacker free paths using Particle Swarm Optimization (PSO) algorithm. Simulation results show that the performance of the proposed approach improves energy efficiency and network lifetime of the network.

Sufficient stabilizing bit rate conditions for an [formula omitted]-dimensional nonlinear system based on event triggering

This paper investigates the problem of stabilizing an n-dimensional nonlinear system whose feedback packets are transmitted via the digital network. In the presence of the bounded processing delay and network delay, the sampling time instant of a feedback packet is not the same as its receiving time instant. The larger difference between these time instants, the higher bit rate is required to stabilize the concerned system. Moreover, not only these delays, but also feedback dropouts and process noise will deteriorate the system performance. Thus we propose a model-based event-triggered control method to stabilize the system and save the occupied network bandwidth. Besides the transmission bits inside the feedback packets, their sampling time instants also convey the state information. The proposed event-triggered method can make full use of the feedback packets, especially their receiving time instant information. Compared with the periodic sampling method, our method performs better and requires lower stabilizing bit rates while the desired input-to-state stability can still be ensured. The obtained bit rate conditions only depend on the Lipschitz constant, the upper bounds of the delays and the dropout rate, and are independent of the bounded process noise.

Event-Triggered Stabilization of a Linear System With Model Uncertainty and i.i.d. Feedback Dropouts.

This article investigates the input-to-state stability (ISS) of continuous-time networked control systems with model uncertainty and bounded noise based on event triggering. The feedback loop is closed over an unreliable digital communication network. Feedback packets suffer from network delay and may be dropped in an independent and identically distributed (i.i.d.) way, which may harm to the concerned stability. This article focuses on a Lyapunov-based event-triggered control design scheme with the consideration of i.i.d. packet dropouts. By designing a state-dependent event-triggering threshold and updating methods, it can still ensure ISS for the concerned multidimensional system in the presence of i.i.d. packet dropouts and model uncertainty without exhibiting the Zeno behavior. Simulations are done to verify the effectiveness of the achieved results.

Bit-Rate Conditions for the Consensus of Quantized Multiagent Systems Based on Event Triggering.

This article investigates the asymptotic consensus problem for multiple discrete-time agents with general dynamics under event-triggered sampling. In such multiagent systems (MASs), the information exchanged between neighboring agents is quantized and transmitted through a digital communication network. Due to the limited bandwidth, it is impossible for agents to capture the precise states of neighbors and only their quantized version can be received, which may degrade or even break the consensus of these MASs. In order to ensure the desired consensus and save the occupied network bandwidth, a model-based event-triggering strategy is well co-designed with a dynamic quantization method. Under the proposed strategy, the error between the real state and its estimated version at neighbors is always bounded by an event-triggering function, which is also taken to compute an upper bound on the control inputs of all agents. We derive a sufficient bit-rate condition required for the desired asymptotic consensus. That condition is mainly determined by the dynamics and communication network topology of agents. Since our event-triggering strategy takes advantage of the extra information extracted from the event-triggering time instants of all feedback packets, the derived bit rate can be lower than that of the conventional periodic sampling strategies, while still ensuring the consensus of the concerned MAS. Simulations are done to illustrate the advantages of the derived bit-rate condition.

Delay and Energy Consumption Analysis of Frame Slotted ALOHA variants for Massive Data Collection in Internet-of-Things Scenarios

This paper models and evaluates three FSA-based (Frame Slotted ALOHA) MAC (Medium Access Control) protocols, namely, FSA-ACK (FSA with ACKnowledgements), FSA-FBP (FSA with FeedBack Packets) and DFSA (Dynamic FSA). The protocols are modeled using an AMC (Absorbing Markov Chain), which allows to derive analytic expressions for the average packet delay, as well as the energy consumption of both the network coordinator and the end-devices. The results, based on computer simulations, show that the analytic model is accurate and outline the benefits of DFSA. In terms of delay, DFSA provides a reduction of 17% (FSA-FBP) and 32% (FSA-ACK), whereas in terms of energy consumption DFSA provides savings of 23% (FSA-FBP) and 28% (FSA-ACK) for the coordinator and savings of 50% (FSA-FBP) and 24% (FSA-ACK) for end-devices. Finally, the paper provides insights on how to configure each FSA variant depending on the network parameters, i.e., depending on the number of end-devices, to minimize delay and energy expenditure. This is specially interesting for massive data collection in IoT (Internet-of-Things) scenarios, which typically rely on FSA-based protocols and where the operation has to be optimized to support a large number of devices with stringent energy consumption requirements.

Necessary and Sufficient Bit Rate Conditions to Stabilize a Scalar Continuous-Time LTI System Based on Event Triggering

This paper considers a scalar continuous-time linear time-invariant system, whose feedback signal is transmitted through a communication network. Such a network has only finite bit rate and suffers from transmission delay which is characterized by both lower and upper delay bounds. The concerned system implements event-triggering strategies, i.e., only when certain events are triggered, the system samples and transmits feedback signals. This paper first derives some lower bounds on the feedback bit rate required to achieve the input-to-state stability under arbitrary event-triggering strategies. Then this paper proposes some constructive methods to design the event-triggering strategy and the controller, and can achieve the input-to-state stability at a bit rate being arbitrarily close to these obtained lower bit rate bounds. Moreover, this paper proves that the stabilizing bit rates under the proposed event-triggering strategies can be strictly lower than the stabilizing bit rate required by any time-triggering strategy. This bit rate superiority comes from the fact that under event triggering, the state information can be freely extracted from the receive time instants of feedback packets without consuming any bit rate. Simulations are done to demonstrate the bit rate superiority of the proposed event-triggering strategies.

Bit rate conditions to stabilize an uncertain scalar continuous‐time linear system with clock offset

SummaryThis paper aims to stabilize a scalar continuous‐time linear system that transmits its feedback information through a digital communication network. The finite bit rate of the feedback network plays a critical role in the input‐to‐state stability of that system. Stabilizing bit rate conditions depend on not only the system matrix but also the uncertainty of the system matrix and the unknown clock offset between the transmitter (sensor) and the receiver (controller). Compared with the current literature, this paper can handle the system matrix uncertainty and clock offset through implementing an event‐triggered sampling strategy and derive stabilizing conditions that require lower bit rates than those of periodic sampling strategies. Such bit rate saving mainly comes from the fact that our event‐triggered strategy can extract state information from the receive time instants of feedback packets without any extra communication cost. Simulations are done to confirm the effectiveness of the obtained stabilizing bit rate conditions.

Sufficient bit rate conditions to stabilize an uncertain scalar nonlinear system based on event triggering

This paper considers to stabilize an uncertain scalar continuous-time nonlinear system with bounded network delay and process noise, which transmits all feedback signals through a digital communication network. In order to save the bandwidth of the feedback network, stability is expected to be maintained at as low as possible feedback bit rate. Based on event triggering, this paper proposes a model-based event-triggered sampling strategy to guarantee the desired input-to-state stability of the concerned system. Due to the bounded network delay, the receiving time instant of a feedback packet cannot be precisely controlled by the sensor, i.e., the receiving time instant is not always equal to its sampling time instant. Their gap, i.e., the network delay, determines how much information can be carried through the receiving time instant and makes great impact on the system’s stability. Sufficient bit rate conditions to stabilize that system are derived. The conditions are determined by the parameter of Lipschitz condition, the upper bound of the network delay and the system uncertainty. Compared with the periodic sampling strategies, a lower bit rate is required by the proposed event-triggered strategy. Simulations are done to verify the effectiveness of the achieved stabilizing bit rate conditions.

Periodic Event-Triggered Quantization Policy Design for a Scalar LTI System With i.i.d. Feedback Dropouts

This technical note proposes an event-triggered quantization policy design method to stabilize a scalar continuous-time linear time-invariant (LTI) system, whose feedback loop is closed over an unreliable digital communication network. The feedback packets suffer from network delay and may be dropped in an independent and identically distributed (i.i.d.) way. In order to save quantization bit rate, we implement a periodic event-triggering strategy which periodically samples the state and only quantizes and transmits the sampled state when a predefined event is triggered. By making good use of both the information bits and the sampling time instants of the feedback packets, our policy can obtain the desired mean-square stability at a lower bit rate than the conventional time-triggered quantization policies which utilize only the information bits inside the feedback packets. Under our quantization policy, the stabilizing bit rate condition is up to the dropout rate, the processing and network delays and the unstable eigenvalue of the system, and is independent of the bounded process noise.

Distributed Receding Horizon Control of Constrained Networked Leader–Follower Formations Subject to Packet Dropouts

A novel receding horizon control scheme is presented in this paper to manage networked leader–follower formation control problems in the presence of time-varying delay and data loss (measurement and feedback packet dropouts) occurrences on the communication and feedback channels. One of the main novelties of the proposed paradigm relies on the use of reachability analysis concepts involving the capability to combine sequences of predecessor sets with polyhedral piecewise state-space partitions. The predecessor sets are here derived offline by taking into account the prescribed state and input constraints, the interconnected nature of the system and the time delay induced by the network latency. They are used online to compute admissible and optimal control actions via a distributed receding horizon computational paradigm. Feasibility, uniformly ultimate boundedness and constraints satisfaction are formally proved regardless of any bounded time delays.

A Microbial Inspired Routing Protocol for VANETs

We present a bio-inspired unicast routing protocol for vehicular ad hoc networks which uses the cellular attractor selection mechanism to select next hops. The proposed unicast routing protocol based on attractor selecting (URAS) is an opportunistic routing protocol, which is able to change itself adaptively to the complex and dynamic environment by routing feedback packets. We further employ a multiattribute decision-making strategy, the technique for order preference by similarity to an ideal solution, to reduce the number of redundant candidates for next-hop selection, so as to enhance the performance of attractor selection mechanism. Once the routing path is found, URAS maintains the current path or finds another better path adaptively based on the performance of current path, that is, it can self-evolution until the best routing path is found. Our simulation study compares the proposed solution with the state-of-the-art schemes, and shows the robustness and effectiveness of the proposed routing protocol and the significant performance improvement, in terms of packet delivery, end-to-end delay, and congestion, over the conventional method.

Bit-Rate Conditions to Stabilize a Continuous-Time Linear System With Feedback Dropouts

This technical note considers the input-to-state stability of a continuous-time linear system, which sends feedback signals from the sensor to the controller over a nondeterministic communication network with bounded network delay and occasional dropouts. Not only the bits inside each feedback packet, but also the sampling time instant of that packet can carry information. Due to processing delay and network delay, the controller cannot precisely know the sampling time of a packet and can only approximate it with the receive time instant of that packet. The difference between the sampling and receive time instants of a packet is referred to as timing error, which reduces the amount of information extracted from the receive time instant. By additionally extracting information from receive time instants of feedback packets, we may stabilize the concerned system in the input-to-state sense at a lower bit rate than the approaches utilizing only the bits inside feedback packets. Besides timing error, nondeterministic dropouts of feedback packets may also harm the stability of the concerned system. By simultaneously considering timing error and feedback dropouts, we derive some stabilizing bit-rate conditions that are determined by the unstable eigenvalues of the system matrix, the dropout rate, and the upper bound on the timing error. These stabilizing bit-rate conditions are not disturbed by bounded process noise.

Adaptive Coding Optimization in Wireless Networks: Design and Implementation Aspects

A fundamental challenge in wireless networks is how to handle packet loss due to noise, interference, and dynamic channel effects, especially when there is no per-packet acknowledgement due to additional delay and potential loss of feedback packets. We design and implement a packet coding optimization scheme, applied at the source node, to enhance end-to-end transmission reliability in a lossy multi-hop network. Specifically, each source node transmits a file of packets to its destination node in the network where the end-to-end packet acknowledgement is not readily available because of the possible error or delay effects over multiple hops. By simply retransmitting packets, a source node cannot guarantee innovative packet arrivals at the destination node. Thus, we design an optimization scheme for adaptive packet coding applied at the source node to avoid transmitting redundant packets, thereby significantly improving the throughput, even for the case of a single unicast session. This scheme does not require any knowledge of network topology and can seamlessly operate with any routing or network coding protocol used at the intermediate relay nodes. We analyze the throughput properties of coded transmissions and verify the feasibility of performance gains via simulations. Then, we provide high fidelity emulation testbed results with real radio transmissions over emulated channels to evaluate the throughput gains. Without relying on end-to-end acknowledgment for each packet, we show that the adaptive packet coding optimization scheme can achieve significantly higher throughput than the retransmission scheme in lossy networks with unicast traffic.