Underlying Communication Network Research Articles

Effective Dynamic Coverage Control for Heterogeneous Driftless Control Affine Systems

To dynamically monitor areas of interest by a group of mobile robots, an effective coverage control strategy for heterogeneous driftless control affine systems is developed in this letter. The coverage strategy guides the robot to move in the direction of the effective coverage and escape the saddle point when the loss function stops descending. In addition, the connectivity of the underlying communication network of the robots is maintained during coverage control. Simulation validates the effectiveness of our proposed coverage strategy.

Performance Analysis of IEC 61850 Messages in LTE Communication for Reactive Power Management in Microgrids

Reactive power management in microgrids with high penetration of distributed renewable energy sources (DRESs) is challenging. The intermittent generation of DRES makes the power management cumbersome. Generally, Flexible AC Transmission System (FACTS) devices such as Distribution Static Compensator (DSTATCOM) are employed for reactive power compensation in microgrids. However, for effective results in microgrids, coordinated operation between DSTATCOM and Distributed Energy Resources (DERs) is required. In this paper, IEC 61850 communication is proposed for realizing coordinated operation between microgrid controller (MGCC), DSTATCOM and DERs. In microgrids, there may be large number of DERs dispersed over a large area. Hence, the underlying communication network technology for IEC 61850 communication must be highly scalable with wide range. Recently developed communication technology Long Term Evolution (LTE) is a promising solution since it offers high data rates, reliability, scalability and longer range. In this paper, the developed IEC 61850 based reactive power management system is tested with the LTE technology and the performance evaluation tests have been performed. Firstly, IEC 61850 messages have been mapped on LTE stack to enable their transmission. Then, simulations over a network emulator have been performed to evaluate the performance of IEC 61850 communication message exchanges over LTE network in terms of End to End (ETE) delays.

\u201cEvacuate everyone south of that line\u201d Analyzing structural communication patterns during natural disasters

In this paper, we analyze more than 16 million tweets that have been sent from 6.1 million Twitter accounts and are related to nine natural disasters. As part of our analysis, we identify eight basic emotions conveyed in these tweets. We found that during natural disasters, social media messages at first predominantly express fear, while sadness and positive emotions increase in the immediate aftermath of the event. In this context, positive emotions contribute to the social phenomenon of emotional bonding and are often related to compassion, gratitude, as well as donations for disaster relief. In our analysis, we found that the users’ emotional expressions directly contribute to the emergence of the underlying communication network. In particular, we identified statistically significant structural patterns that we call emotion-exchange motifs and show that: (1) the motifs 021U and 021D are common for the communication of all eight emotions considered in this study, (2) motifs which include bidirectional edges (i.e. online conversations) are generally not characteristic for the communication of surprise, sadness, and disgust, (3) the structural analysis of a set of emotions (rather than a single emotion) leads to the formation of more complex motifs representing more complex social interactions, and (4) the messaging patterns emerging from the communication of joy and sadness show the highest structural similarity, even reaching a perfect similarity score at some point during the data-extraction period.

ICASM: An Information-Centric Network Architecture for Wide Area Measurement Systems

Wide Area Measurement Systems (WAMS) use an underlying communication network to collect and analyze data from devices in the power grid, aimed to improve grid operations. For WAMS to be effective, the communication network needs to support low packet latency and low packet losses. Internet Protocol (IP), the pervasive technology used in today's communication networks uses loop-free best-paths for data forwarding, which increases the load on these paths causing delays and losses in delivery. Information-Centric Networking (ICN), a new networking paradigm, designed to enable a data-centric information sharing, natively supports the concurrent use of multiple transmission interfaces, in-networking caching, as well as per-packet security and can provide better application support. In this paper, we present iCASM, an ICN-based network architecture for wide area smart grid communications. We demonstrate through simulations that iCASM achieves low latency and 100% data delivery even during network congestion by leveraging multiple available paths; thus significantly improving communication resiliency in comparison to an IP-based approach. iCASM can be used immediately on today's Internet as an overlay.

Remote Monitoring of Electric Vehicle Charging Stations in Smart Campus Parking Lot

Smart parking lots are smart places capable of supporting both parking and charging services for electric vehicles (EVs). In order to manage EV charging, the parking lot local controller (PLLC) requires data exchange with EV charging stations (EVCSs) through communication infrastructures. However, data losses and communication delays are unavoidable and may significantly degrade the system performance. This work aims to investigate the underlying communication networks for remote monitoring of EVCSs in a smart campus parking lot. The communication network consists of two subnetworks: parking area network (PAN) and campus area network (CAN). PAN covers communication among EVs, charging stations and PLLC, while CAN enables dedicated communication between PLLCs and a global controller of the university. As one of the major obstacles in EV system is the lack of unified communication architecture to integrate EVCS in the power grid, we develope communication models for the in-vehicle system and EVCSs based on logical node concept of IEC 61850 standard. Furthermore, we implement network models for EVCSs using OPNET modeler. Different communication technologies and configurations are considered in modeling and simulations, and end-to-end delay is evaluated and discussed.

Survey, comparison and research challenges of IoT application protocols for smart farming

Smart farming era has already begun and its societal and environmental implications are expected to be huge. In this context, the Internet of Things (IoT) technologies have become the major path forward towards novel farming practices. The unprecedented capability of data collection and management offered by IoT is based on several factors of the underlying communication network architecture and technology, one of the most important being the application level protocol that is used among IoT nodes, gateways, and application servers. This work offers an up-to-date survey of research efforts on the IoT application layer protocols, focusing on their basic characteristics, their performance as well as their recent use in agricultural applications. Furthermore, it provides a comparison among them, in terms of well-accepted key performance indicators and comments on their suitability in the framework of smart farming as well as the corresponding challenges that have to be faced towards their efficient implementation.

Polynomial Silent Self-Stabilizing p-Star Decomposition†

Abstract We present a silent self-stabilizing distributed algorithm computing a maximal $\ p$-star decomposition of the underlying communication network. Under the unfair distributed scheduler, the most general scheduler model, the algorithm converges in at most $12\Delta m + \mathcal{O}(m+n)$ moves, where $m$ is the number of edges, $n$ is the number of nodes and $\Delta $ is the maximum node degree. Regarding the time complexity, we obtain the following results: our algorithm outperforms the previously known best algorithm by a factor of $\Delta $ with respect to the move complexity. While the round complexity for the previous algorithm was unknown, we show a $5\big \lfloor \frac{n}{p+1} \big \rfloor +5$ bound for our algorithm.

A consensus-based robust secondary voltage and frequency control scheme for islanded microgrids

This paper deals with the problem of designing a fully-distributed and robust secondary control scheme for voltage and frequency restoration of islanded microgrids along with real power sharing. Compared to the existing developments in this topic, the proposed multi-agent consensus-based secondary control scheme takes into account the effects of model uncertainty, parameter variation and unmodelled dynamics and thereby, offers a certain degree of robustness against all these factors. Due to virtue of the fully-distributed control configuration, each distributed generating (DG) unit in a microgrid requires only the information of its own and some of its neighbours but not of all other DG units attached to that microgrid. This helps in reducing the bandwidth requirement and cost of the underlying communication network and also causes enhanced flexibility and reliability of the overall microgrid operation. The proposed scheme counteracts any fluctuation in the terminal voltage and frequency of the DG units and also facilitates real power sharing among them at a pre-specified ratio despite the time-varying load disturbances, various power line faults, communication delays, etc. Finally, an exhaustive case study on a prototype IEEE 14-bus microgrid system containing five DG units has been accomplished to demonstrate the usefulness of the developed scheme.

The Effect of Cellular Network-Based Communication Delays in an EV Aggregator’s Domain on Frequency Regulation Service

Provision of frequency regulation service with a large number of electric vehicles (EVs) through EV aggregators requires to exchange regulation related messages through communication infrastructures in EV aggregators’ domain. Communication delays in the aggregators’ domain may significantly affect regulation performance. We investigate the effect of communication delays in an EV aggregator’s domain on the regulation performance. We present an underlying communication network for the EV aggregator controlling a group of EVs at a parking lot. The underlying communication network consists of two separate subnetworks: 1) a power line communication network between a pair of EV and EV supply equipment (EVSE) and 2) an LTE network between one EV aggregator and a group of EVSEs. In order to evaluate the delay effect on the regulation performance, we propose a co-simulation platform which is composed of an LTE network model and a load frequency control model. For the LTE network, we analyze the potential sources of delays and identify the repeated service request and release procedures as a critical delay source. We implement the identified repeated procedure by using network simulator-3 and evaluate the delay performance of frequency regulation service. We evaluate the effect of the communication delay in the EV aggregator’s domain on regulation performance.

Delay and cooperation in nonstochastic bandits

We study networks of communicating learning agents that cooperate to solve a common nonstochastic bandit problem. Agents use an underlying communication network to get messages about actions select...

On Characterizing Information Dissemination During City-Wide Cascading Failures in Smart Grid

Although the smart gird is expected to eliminate cascading failures with the help of real-time system monitoring and control, it is yet unknown whether its underlying communication network is fast and reliable enough to achieve this goal. In this paper, we take an in-depth study on this issue by addressing three specific questions: 1) what is the evolution process of information dissemination and fault propagation in the smart grid?; 2) how to quantify the impact of cascading failures?; and 3) what are the conditions that information dissemination becomes either a booster or an adversary in mitigating cascading failures? To answer these questions, we build an innovative framework, the cascading failure with communications framework, to consolidate both communication networks and power grids, and provide quantitative evaluation on the impact of cascading failures. By studying and observing the progress of cascading failures in two city-wide power grids, we find that information dissemination is not always the winner in the race against fault propagation. Particularly, while fast and reliable communications can help in mitigating the consequences of cascading failures, anomalies such as massage delays may weaken its capability. Moreover, severely under-achieved communications, counter-intuitively, can even exacerbate the consequence of cascading failures.

Graph reconstruction from path correlation data

A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured on a set of intersecting paths between a subset of boundary vertices, and even the underlying graph when this is not known. In particular, temporal correlations between path metrics have been used to infer composite weights on the subpath formed by the path intersection. We call these subpath weights the path correlation data.In this paper we ask the following question: when can the underlying weighted graph be recovered knowing only the boundary vertices and the path correlation data? We establish necessary and sufficient conditions for a graph to be reconstructible from this information, and describe an algorithm to perform the reconstruction. Subject to our conditions, the result applies to directed graphs with asymmetric edge weights, and accommodates paths arising from asymmetric routing in the underlying communication network. We also describe the relationship between the graph produced by our algorithm and the true graph in the case that our conditions are not satisfied.

Adaptive Reliable Coordination Control for Linear Agent Networks With Intermittent Communication Constraints

This paper studies the adaptive reliable coordination control problem for a class of multiagent systems under time-varying topology in the presence of intermittent communication constraints and actuator faults. The underlying communication network is assumed to switch among finite undirected connected graphs. A new fault-tolerant consensus tracking control scheme is presented by utilizing the distributed adaptive technique. In contrast to the existing results on the cooperative tracking control problem against intermittent communications, no assumption on zero input of the leader is made in the discussions. By introducing the estimates to account for the unknown faulty efficiency factors and the bounds of the leader's control input signal, the local controller parameters are updated in individual nodes. Also, a novel topology-allocation-dependent average dwell time approach is proposed to deal with network switching jumps effectively. By combining multiple Lyapunov functions method and algebraic graph theory, it is shown that the global tracking errors are uniformly ultimately bounded even in the cases of intermittent communication constraints and actuator failures. Finally, the simulation study demonstrates the effectiveness of the proposed reliable coordination control strategy.

Game Theoretic Spectrum Allocation in Femtocell Networks for Smart Electric Distribution Grids

Ever growing penetration of the behind-the-meter technologies is changing the electricity consumption profiles of end-users. Intelligent coordination of these emerging technologies through a robust communication infrastructure enables their seamless integration with electric utilities’ operation. In this context, an efficient and reliable communication infrastructure plays a pivotal role in enabling optimal integration of emerging resources. In this paper, we propose a game-theory based method to enhance efficiency of the underlying communication network. Specifically, we focus on Femtocell communication technology which is one the promising options for improving poor indoor communication coverage. The major drawback for using femtocell communication technology is cross-layer interference of femto users (FUs) and macro users (MUs) which adversely impact network performance. In this paper, we propose a novel approach for sharing spectrum in a cognitive radio system with FUs and MUs as primary and secondary users, respectively. The underlying problem is formulated as Stackelberg game that is joined with a convex optimization problem. In this study, MUs and FUs are assumed to be selfish, rational and motivated to achieve maximum utility function, while MUs are competing to obtain maximum bandwidth. Finally, we present a closed form solution for the proposed approach which obtains a unique Nash Equilibrium and prioritizes the access of MUs to femto-base stations. Simulation results provide proof of concept and verify the effectiveness of our mathematical modeling.

Distributed wide-area control of power system oscillations under communication and actuation constraints

In this paper a distributed Model Predictive Control design is presented for inter-area oscillation damping in power systems under two critical cyber–physical constraints — namely, communication constraints that lead to sparsification of the underlying communication network, and actuation constraints that respect the saturation limits of generator controllers. In the current state-of-art, distributed controllers in power systems are executed over fixed communication topologies that are most often agnostic of the magnitude and location of the incoming disturbance signals. This often leads to a sub-optimal closed-loop performance. In contrast, the communication topology for the proposed controller is selected in real-time after a disturbance event based on event-specific correlations of the generator states with the dominant oscillation modes that are excited by that event. Since these correlations can differ from one event to another, so can the choice of the communication topology. These correlations are used to identify the most important sets of generators that must exchange state information for enhancing closed-loop damping of the inter-area modal frequencies. Effectiveness of this strategy is shown via simulations on the 48-machine, 140-bus model for the Northeast Power Coordinating Council.

Enhanced class based dynamic priority scheduling to support uplink IoT traffic in LTE-A networks

Internet of Things (IoT) has now become a common term in technological communities. Machine-to-machine communications (M2M) is one of the components of IoT which deals with communication of devices to device and device to the network aspects. LTE-A networks have emerged as one of the preferred underlying communication networks to support IoT or M2M traffic. However, the uplink packet scheduling to optimize the QoS (quality of service) of M2M traffic without affecting or least affecting the QoS of Human-to-human (H2H) traffic (traffic generated by regular users (also called as H2H users) such as smartphone traffic, Internet traffic, voice traffic, etc.) is one of the main challenges in LTE-A networks. As a solution, we propose an uplink packet scheduling algorithm, called as enhanced class based dynamic priority (E-CBDP) algorithm, which ensures the QoS of H2H traffic by giving it priority over M2M traffic but, optimizes the QoS of M2M traffic by pushing the scheduling of H2H traffic to their delay boundaries. Further, a dynamic M2M traffic control threshold is defined to enable the operator for proactive regulation of the huge M2M traffic to avoid network congestion as well as to minimise the impact on H2H traffic. We characterize the proposed scheduling algorithm via a mathematical analysis for the metrics such as average length of the H2H queue, average length of the M2M queue, average waiting time of H2H packets, and average waiting time of M2M packets. We compare the performance of E-CBDP algorithm with some recent solutions in terms of average delay, percentage of packets dropped, aggregate throughput, fairness, and energy consumption. Simulation results show that E-CBDP algorithm demonstrates excellent performance in terms of packet drop rate and fairness while provides satisfactory performance in terms of delay, throughput, and energy consumption.

A Co-Simulation Framework for Integrated Planning and Analysis of Wide Area Measurement and Protection Systems

The recent efforts to extend measurement and communication infrastructures in power grids have brought about new potentials for a more efficient and optimized grid operation using the data which become available. Due to this integration, on the other hand, not only the network expansion and planning but also the development of new applications must be carried out under consideration of the interdependencies between the power grid and the underlying communication network. In this work, we present a co-simulation environment and tool chain to enable integrated planning and subsequent performance analysis of a wide area measurement system. In the first part of the paper, we investigate the performance of PMU-based state estimation techniques under several power system and communication network scenarios. In the second part of the paper, furthermore, the presented setup is extended for co-simulative investigations of the machine learning-based fault detection and classification techniques in power systems. The presented results not only validate the developed software solution for similar research studies but also scrutinize the impact of communication network performance on power system state estimation and PMU-based decision-making for fault detection and classification.

Distributed optimization on random graphs

Abstract We consider the distributed optimization problem for the sum of convex functions where the underlying communications network connecting agents at each time is drawn at random from a collection of directed graphs. We propose a modified version of the subgradient-push algorithm that is provably almost surely convergent to an optimizer on any such sequence of random directed graphs, establishing the first of this kind.

Distributed Optimal Dispatch of Distributed Energy Resources Over Lossy Communication Networks

Driven by smart grid technologies, a great effort has been made in developing distributed energy resources (DERs) in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient control and coordination in order to harvest their potential benefits. In this paper, we consider optimal DER coordination problem, where the goal is to minimize the total generation cost while meeting total demand and satisfying individual generator output limit. This paper develops a distributed algorithm for solving the optimal DER coordination problem over lossy communication networks with packet-dropping communication links. Under the assumption that the underlying communication network is strongly connected with a positive probability and the packet drops are independent and identically distributed, we show that the proposed algorithm is able to solve the optimal DER coordination problem even in the presence of packet drops. Numerical simulation results are used to validate and illustrate the proposed algorithm.

Communicating with sentences: A multi-word naming game model

Naming game simulates the process of naming an object by a single word, in which a population of communicating agents can reach global consensus asymptotically through iteratively pair-wise conversations. We propose an extension of the single-word model to a multi-word naming game (MWNG), simulating the case of describing a complex object by a sentence (multiple words). Words are defined in categories, and then organized as sentences by combining them from different categories. We refer to a formatted combination of several words as a pattern. In such an MWNG, through a pair-wise conversation, it requires the hearer to achieve consensus with the speaker with respect to both every single word in the sentence as well as the sentence pattern, so as to guarantee the correct meaning of the saying; otherwise, they fail reaching consensus in the interaction. We validate the model in three typical topologies as the underlying communication network, and employ both conventional and man-designed patterns in performing the MWNG.