Control Information Exchange Research Articles

Information control in networked discrete event systems

How to control information exchange among different users is an important problem in networked systems with many users/agents. Generally speaking, there are several considerations in control of information exchange in a networked system, including (1) to ensure a friend user has sufficient information to perform its tasks, (2) to deprive an adversary user its information to perform its tasks, (3) to minimize information exchange among friend users so that the risk of information leaking is minimized, and (4) to maximize information broadcasted to all users to achieve maximum transparency. In this paper, we investigate the information control problems in the framework of discrete event systems. Based on the problem at hand, we divide users in a networked system into two or more groups. Users in the same group are consider as friends and users in a different group are consider as adversaries. Several information control problems are investigated and solved using a systematic and rigorous approach. Methods are developed to design controllers that send minimum information to its friends to help them to perform their tasks and broadcast maximum information without helping its adversaries.

Sub-6 GHz V2X-assisted MmWave optimal scheduling for vehicular networks

Sub-6 GHz assisted millimeter wave (mmWave) technology is a promising solution to address the ever-increasing data exchange demand in Vehicle-to-Everything (V2X) communication. The omni-directional sub-6 GHz channels exchange vehicle and control information in the vehicular network, while the directional mmWave technology is used for high-rate data transmission. Consider the huge amounts of vehicular data, the transmission constraints imposed by mmWave, and the unique vehicular ad hoc network (VANET) data features, a sub-6 GHz assisted-mmWave scheduling algorithm is needed to facilitate V2X data transmission. Existing scheduling algorithms in the literature fall short of addressing realistic V2X data features. Therefore, in this paper, we propose a novel objective to maximize the network utility that succinctly captures realistic V2X data features, including varying data sizes, data importance and their freshness decay with transmission delay. We formulate the scheduling problem into a novel mixed-integer sum-of-ratios optimization problem. To solve the challenging NP-complete problem, we first derive an equivalent parametric mixed-integer linear programming problem with existence and uniqueness proofs. Next, we provide the necessary condition for the optimality of the equivalent problem. A novel Parameterization-based Iterative Algorithm (PIA) is then developed to learn the global optimal solution with convergence analysis. Comparative simulation studies with the brute-force algorithm, the widely used branch and bound (BB) method, the greedy algorithm, and our previously developed maximum weight matching based iterative algorithm (MWMIA) are conducted to verify the correctness and effectiveness of the proposed PIA scheduling algorithm.

An imperfect spectrum sensing-based multi-hop clustering routing protocol for cognitive radio sensor networks

Multi-hop clustering routing protocols are potential solutions to achieve effective and energy-efficient data delivery in cognitive radio sensor networks (CRSNs). Current clustering routing protocols for CRSNs generally assume perfect spectrum sensing, i.e., false alarm and missed detection are ignored, which may result in collisions with primary users and transmission failure or constrained spectrum usage. To alleviate the impact of imperfect spectrum sensing on network performance, an imperfect spectrum sensing-based multi-hop clustering routing protocol (ISSMCRP) is proposed for CRSNs in this paper. Cluster head (CH) and relay selection criteria are defined based on detection level function of available channels to help select CHs and relays with high spectrum sensing capability. Idle detection accuracy-based intra-cluster and inter-cluster channel selection criterion is proposed to promote successful intra-cluster and inter-cluster data delivery. In addition, control overhead introduced by CHs selection and cluster formation is strictly controlled, and reasonable cluster radii are set to manage the range of control information exchange, so as to reduce the energy consumption caused by control overhead. Simulation results show that compared with the existing clustering routing protocols for CRSNs, ISSMCRP gains obvious advantages in expanding the network lifespan and enhancing the network surveillance capability.

An Energy Balance-Oriented Clustering Routing Protocol for Cognitive Radio Sensor Networks

Uneven clustering is an effective solution to solve the energy hole problem in multihop cognitive radio sensor networks (CRSNs). However, current literature leaves control overhead and multihop intercluster routing out of consideration and adopts constant weight coefficients for cluster radius calculation instead of reasonably setting their values according to specific network configurations. To solve the above problems, a distributed energy balance-oriented uneven clustering routing protocol (EBUCRP) is proposed in this article. First, by fully considering the energy consumption of control information exchange and data transmission, EBUCRP theoretically derives the optimal cluster radius of each unit within which distributed clusters are formed. Second, communication capability-based selection criteria are defined from joint energy and spectral efficiency perspectives to help select high-quality cluster heads and next-hop relays. In this case, the monitoring information can be transferred to the sink through efficient intracluster data aggregation and intercluster multihop forwarding. Third, EBUCRP strictly restricts the energy consumption of control information exchange during network operation. Simulation results show that EBUCRP gains obvious advantages over competing protocols in enhancing the lifetime and supervision capability of both single-hop and multihop CRSNs.

Multi-agent robotic system (MARS) for UAV-UGV path planning and automatic sensory data collection in cluttered environments

There has been growing interest in increasing the application of robotic and automation technologies for building indoor inspection. However, much previous research on indoor robotic applications was limited to a single type of unmanned aerial/ground vehicle (UAV/UGV), each of which has certain limitations and constraints. Besides, the robotic systems suffer from inefficient control within cluttered indoor environments containing many obstacles. This paper presents a multi-agent robotic system (MARS) for automatic UAV-UGV path planning and indoor navigation to automate sensory data collection. The proposed MARS consists of a new system architecture that defines the attributes and data requirements for UAV and UGV indoor path planning. To improve indoor navigation in cluttered environments, an enhanced shunting short-term memory model is established to optimize the pathfinding of UAV/UGV for data collection. Assessment of indoor navigation is conducted with a simulation-based approach and LiDAR SLAM. A mediating agent, which harnesses a control algorithm and information exchange mechanism, is proposed to interoperate UAV and UGV for automated data collection. The proposed new MARS is examined in experiments, in which a single UAV, dual UAVs, and combined UAV-UGV are tested in a research laboratory. The result indicates that the MARS can support automated path planning and indoor navigation for 2D image and 3D point cloud data collection.

CQI Prediction Through Recurrent Neural Network for UAV Control Information Exchange Under URLLC Regime

Unmanned aerial vehicles (UAVs) control information delivery is a critical communication with stringent requirements in terms of reliability and latency. In this context, link adaptation plays an essential role in the fulfillment of the required performance in terms of decode error probability and delay. Link adaptation is usually based on channel quality indicator (CQI) feedback information from the user equipment that should represent the current state of the channel. However, measurement, scheduling and processing delays introduce a CQI aging effect, that is a mismatch between the current channel state and its CQI representation. Using outdated CQI values may lead to the selection of a wrong modulation and coding scheme, with a detrimental effect on performance. This is particularly relevant in ultra reliable and low latency communications (URLLC), where the control of the reliability can be negatively impacted, and it is more evident when the channel is fast varying as the case of UAVs. This paper analyzes the effects of CQI aging on URLLCs, considering transmissions under the finite blocklength regime, that characterizes such communications type. A deep learning approach is investigated to predict the next CQI from the knowledge of past reports, and performance in terms of decode error probability and throughput is given. The results show the benefit of CQI proposed prediction mechanism also in comparison with previously proposed methods.

Impact of MAC Layer on The Hidden and Exposed Terminal Problem in MANET

Wireless networking grows rapidly because of the human desires for mobility and for freedom from tethers, i.e., from physical connections to communication networks. Recent advances in wireless technology have equipped portable computers, such as notebook computers and personal digital assistants with wireless interfaces that allow networked communication even while a user is mobile. We will focus on a particular kind of wireless network: mobile ad hoc networks. A mobile ad hoc network is a self organizing and rapidly deployable network in which neither a wired backbone nor a centralized control exists. The network nodes communicate with one another over scarce wireless channels in a multi-hop fashion. The ad hoc network is adaptable to the highly dynamic topology resulted from the mobility of network nodes and the changing propagation conditions. Generally, protocols used at medium access and physical layers of ad hoc networks are similar to those used in infrastructure based wireless networks. It is a common practise in infrastructure based wireless networks to use pre-data exchange of control information to eliminate the hidden terminal" problem.

Event-triggered leader-following formation control for multi-agent systems under communication faults: Application to a fleet of unmanned aerial vehicles

The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems (MASs) under communication faults. All the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the agents. Linear matrix inequalities (LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization error. Based on the closed-loop system, an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy consumption. The proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles (UAVs) under communication faults. A comparison between a state-of-the-art technique and the proposed technique has been provided, demonstrating the performance improvement brought by the proposed approach.

Security Information Sharing in Smart Grids: Persisting Security Audits to the Blockchain

With the transformation in smart grids, power grid companies are becoming increasingly dependent on data networks. Data networks are used to transport information and commands for optimizing power grid operations: Planning, generation, transportation, and distribution. Performing periodic security audits is one of the required tasks for securing networks, and we proposed in a previous work autoauditor, a system to achieve automatic auditing. It was designed according to the specific requirements of power grid companies, such as scaling with the huge number of heterogeneous equipment in power grid companies. Though pentesting and security audits are required for continuous monitoring, collaboration is of utmost importance to fight cyber threats. In this paper we work on the accountability of audit results and explore how the list of audit result records can be included in a blockchain, since blockchains are by design resistant to data modification. Moreover, blockchains endowed with smart contracts functionality boost the automation of both digital evidence gathering, audit, and controlled information exchange. To our knowledge, no such system exists. We perform throughput evaluation to assess the feasibility of the system and show that the system is viable for adaptation to the inventory systems of electrical companies.

Application of Radio Environment Map Reconstruction Techniques to Platoon-based Cellular V2X Communications.

Vehicle platoons involve groups of vehicles travelling together at a constant inter-vehicle distance, with different common benefits such as increasing road efficiency and fuel saving. Vehicle platooning requires highly reliable wireless communications to keep the group structure and carry out coordinated maneuvers in a safe manner. Focusing on infrastructure-assisted cellular vehicle to anything (V2X) communications, the amount of control information to be exchanged between each platoon vehicle and the base station is a critical factor affecting the communication latency. This paper exploits the particular structure and characteristics of platooning to decrease the control information exchange necessary for the channel acquisition stage. More precisely, a scheme based on radio environment map (REM) reconstruction is proposed, where geo-localized received power values are available at only a subset of platoon vehicles, while large-scale channel parameters estimates for the rest of platoon members are provided through the application of spatial Ordinary Kriging (OK) interpolation. Distinctive features of the vehicle platooning use case are explored, such as the optimal patterns of vehicles within the platoon with available REM values for improving the quality of the reconstruction, the need for an accurate semivariogram modeling in OK, or the communication cost when establishing a centralized or a distributed architecture for achieving REM reconstruction. The evaluation results show that OK is able to reconstruct the REM in the platoon with acceptable mean squared estimation error, while reducing the control information for REM acquisition in up to 64% in the best-case scenario.

On the Joint Usage of Target Wake Time and 802.11ba Wake-Up Radio

Energy efficiency is a significant challenge for modern wireless networking devices. It is crucial for the Internet of Things devices, is required for battery-supplied user devices such as smartphones, and is advisable for high-performance devices such as wireless VR headsets. This article examines the ability of modern Wi-Fi devices to achieve extremely low power consumption when they rarely send and receive data. Two recently developed mechanisms, namely Target Wake Time (TWT) and Wake-Up Radio (WUR), are studied. The first one allows stations to schedule the frame exchanges in advance, while the second one introduces a low-power radio for control information exchange. Although TWT and WUR differ significantly, they both suffer from the clock drift effect that significantly degrades their performance in the case of rare traffic. The paper describes these mechanisms, focusing on their revolutionary features, and presents mathematical models to evaluate the impact of this effect on TWT and WUR mechanism efficiency in terms of energy and channel time consumption. The paper also proposes and thoroughly examines various approaches to the joint and separate usage of TWT and WUR in Wi-Fi networks.

Vehicle-Centric Network Association in Heterogeneous Vehicle-to-Vehicle Networks

Safe and reliable operation of future autonomous vehicles requires ultra-low latency vehicle-to-vehicle (V2V) networking. However, due to scalability issues of purely ad hoc network, vehicle-to-infrastructure (V2I) communication is still in demand. To avoid interference between V2V and V2I communications, conventional network association such as handover may generate a large amount of control and signaling overhead, especially in environments with high-speed mobility and small-coverage access points. Taking the additional latency caused by the overhead into consideration, a vehicle-centric approach is proposed to guarantee the low-latency requirements of the V2V networks. Different from solely optimizing the latency performance, the proposed approach focuses on effectively operating the network association and resources re-allocation. This avoids the massive exchange of control information and signaling and reduces its impact on latency. The proposed framework for V2V networking can underlay different virtual cells with a constrained network association rate and we can derive the corresponding upper bound of the latency performance. Analysis and simulation results indicate that our scheme successfully guarantees the upper bound of the latency and simultaneously constrains the network association rate, thus limiting the additional control exchange and signaling overhead.

Difference-Set-Based Channel Hopping for Minimum-Delay Blind Rendezvous in Multi-Radio Cognitive Radio Networks

Rendezvous in the blind fashion is known as one of the most robust and effective ways for cognitive users (CUs) to exchange control information under the dynamic interference of primary users (PUs). Earlier, no existing scheme could guarantee CUs to rendezvous blindly in each timeslot, which makes them experience relatively long exchange delay. Based on the mathematical concept of relaxed cyclic difference set ( DS ), this paper proposes two novel channel hopping (CH) schemes for multi-radio CUs with and without a synchronized time clock to rendezvous blindly in every timeslot. This achievement of minimum rendezvous delay is especially useful for such delay-sensitive applications as real-time voice and emergency communications. Moreover, based on a special class of DS, the proposed two schemes can closely approach the theoretical lower bound on the number of radio transceivers for CUs to rendezvous blindly in every timeslot and, hence, minimizes their required hardware complexity to exchange control information at the minimum rendezvous delay. Numerical simulation shows that, under dynamic PU interference, the proposed schemes outperform the existing ones in terms of the average throughput and delay of CUs.

A Distributed Control Framework for TDM-PON Based 5G Mobile Fronthaul

The 5G mobile fronthaul (MFH) is bound to be overwhelmed by the explosive growth and stringent requirements of future wireless traffic. The time division multiplexed (TDM) passive optical network (PON) is a candidate for supporting such an MFH. Typically, such a TDM-PON utilizes upstream dynamic bandwidth allocation (DBA) schemes that are centralized at a distant central office (CO) which results in a performance that is not best suited for the MFH. Therefore, this work proposes a novel control framework by shifting the centralized DBA tasks away from the CO towards the closely clustered Remote Radio Heads (RRHs). By exploiting the interconnectivity of the RRHs, the access nodes exchange signaling and control information among themselves to facilitate a fully distributed upstream DBA without the involvement of the CO. The proposed framework separates the control plane from the data plane which paves the way for an efficient exchange of control messages, increased available upstream bandwidth and improved cyclic bandwidth allocation. This translates into a TDM-PON based MFH with lower latency, higher utilization and reduced packet loss.

Adaptive Power Control Scheme for Mobile Wireless Sensor Networks

One of the major factors that affects the performance of wireless sensor networks (WSN) is its limited battery capacity. Mobile wireless sensor networks (MWSN) are just like WSN except either sensor nodes or sink or both can move. Similar to WSN nodes, in MWSN have limited power resources, so network life depends on battery power consumption. Most of the energy consumed by the network is when transmitting or exchange of control information and data is performed. There are different techniques presented by the researchers to conserve energy like topology control, power management, and data driven methods, etc. In this paper, an adaptive power control strategy for conserving energy in MWSN is presented. The proposed scheme uses variable transmission power to reduce energy usage in the transmission of data and control packets and estimates the energy consumed in unicast and broadcast communication of data and control packets. Sensor nodes adjust their transmission power level at every stage of communication which not only reduces the energy utilization by the sensor nodes but also increases data reception at the sink. This is achieved by limiting unnecessary transmissions within sensing regions where they are not intended to reach or exist.

CDCSS: cluster-based distributed cooperative spectrum sensing model against primary user emulation (PUE) cyber attacks

In cognitive radio network, the secondary users (SUs) use the spectrum of primary users for communication which arises the security issues. The status of SUs as legitimate users is compulsory for the stability of the system. This paper addresses the issue of delay caused by a band-selection decision process that directly affects the security and performance. The model cluster-based distributed cooperative spectrum sensing is proposed. In this model, cluster heads (CHs) exchange control information with other CHs and ordinary nodes. This model significantly reduced the delay, sensing, convergence, routing, in band-selection process. This also reduces the energy consumption while sensing the spectrum which seriously leads to performance upgradation. The simulated results show the improved performance of cognitive radio networks in terms of delay, packet loss ratio and bandwidth usage as compared to cluster-based cooperative spectrum sensing model. The opportunity for primary user emulation attacker is minimized as the overall delay is reduced.

An Architecture to Manage Incoming Traffic of Inter-Domain Routing Using OpenFlow Networks

The Border Gateway Protocol (BGP) is the current state-of-the-art inter-domain routing between Autonomous Systems (ASes). Although BGP has different mechanisms to manage outbound traffic in an AS domain, it lacks an efficient tool for inbound traffic control from transit ASes such as Internet Service Providers (ISPs). For inter-domain routing, the BGP’s destination-based forwarding paradigm limits the granularity of distributing the network traffic among the multiple paths of the current Internet topology. Thus, this work offered a new architecture to manage incoming traffic in the inter-domain using OpenFlow networks. The architecture explored direct inter-domain communication to exchange control information and the functionalities of the OpenFlow protocol. Based on the achieved results of the size of exchanging messages, the proposed architecture is not only scalable, but also capable of performing load balancing for inbound traffic using different strategies.

Resource Allocation for D2D-Enabled Communications in Vehicle Platooning

Recent studies have shown that traffic safety and efficiency can be substantially improved by vehicle platooning, in which the platoon’ stability is ensured through the exchange of control information among vehicles. So, it is a key issue to share control information efficiently and timely. Proximity-based device-to-device (D2D) communications with high transmission rate, can provide a promising solution to the above issue. In this paper, a platoon leader evaluation-based two-stage platoon formation algorithm is proposed to form stable platoons, which can significantly reduce the spectrum resource overhead and improve the safety of vehicle platooning. After that, we propose a predecessor-following communication mode-based on D2D, ensuring high-rate transmission of control information. Moreover, we propose time division-based intra-platoon and minimum rate guaranteed inter-platoon resource allocation mechanisms, which aims at allocating resources for D2D users efficiently within the platoon and optimize cellular users’ rate, respectively. Numerical results show that the proposed mechanism and algorithm can not only significantly improve spectrum resource utilization, but also guarantee the platoon stability.

Distributed Model Predictive Control and Implementation for Vehicle Active Suspensions

This paper proposes a distributed model predictive control (DMPC) method for a half-vehicle system with active suspensions. First, the half-vehicle system is divided into three subsystems to reduce the system dimension. Considering the distribution characteristics of suspension control systems, a DMPC controller is designed for each suspension subsystem in order to inhibit the vehicle vertical and pitch motion. To evaluate the proposed control system, controllers with low cost micro-control units (MCU) are implemented, where a fast MPC method for real-time optimization based on continuation/general minimum residual (C/GMRES) method is realized and in-vehicle network FlexRay is used to exchange control information among these controllers. Finally, the implementation of DMPC controllers in MCUs is finished and the results show that vehicle comfortability can be improved by the proposed controllers.

Cluster-Based Opportunistic Spectrum Allocation in CRWMN’s Using Co-operative Mechanism

With the innovation of Cognitive Radio Wireless Mesh Network’s, Opportunistic Spectrum Allocation can possibly moderate spectrum lack, by letting Secondary User’s a chance to sense and use unused bits of opportunistic licensed spectrum without any unfavourable effect on the Primary User’s. In Cognitive Radio Wireless Mesh Network’s, the Medium-Access-Control protocols characterizes the utilization of spectrum proficiently by allocating the channels among the users. Majority of proposed Medium-Access-Control protocols are utilizing Common-Control-Channel for dealing with the assets of Secondary-Users. The major downsides of these Medium-Access-Control protocols are broadcasting of Control-channel when substantial number of Secondary-User exists. In contrast with these Medium-Access-Control protocols, we develop an algorithm Time-Slotted-Allocation-Medium-Access-Control (TSA-MAC) protocol which is based on Clustered Time-Division-Medium-Access approach, which permits Secondary-User’s to allocate opportunistic spectrum with the help of co-operative decisions by exchange control information. In this approach, we are dividing the channels as different slots on which Secondary-User’s can transfer control and data packets. The TSA-MAC protocol will enhance the throughput for the Secondary-User’s over the communication channel. And also this method will facilitate to decide and allocate free channels for Secondary-User’s without interfering with Primary User’s.