The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless, and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors toward mobile subscribers, enterprises, and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultralow latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.

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Mobile Edge Computing: A Survey

In this chapter, you will see how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models.” You will also see that if a network flow model has “integer-valued data,” the simplex method finds an optimal solution that is integer-valued.

Flows in Networks

Unmanned aerial vehicles (UAVs) have found numerous applications and are expected to bring fertile business opportunities in the next decade. Among various enabling technologies for UAVs, wireless communication is essential and has drawn significantly growing attention in recent years. Compared to the conventional terrestrial communications, UAVs’ communications face new challenges due to their high altitude above the ground and great flexibility of movement in the 3-D space. Several critical issues arise, including the line-of-sight (LoS) dominant UAV-ground channels and induced strong aerial-terrestrial network interference, the distinct communication quality-of-service (QoS) requirements for UAV control messages versus payload data, the stringent constraints imposed by the size, weight, and power (SWAP) limitations of UAVs, as well as the exploitation of the new design degree of freedom (DoF) brought by the highly controllable 3-D UAV mobility. In this article, we give a tutorial overview of the recent advances in UAV communications to address the above issues, with an emphasis on how to integrate UAVs into the forthcoming fifth-generation (5G) and future cellular networks. In particular, we partition our discussion into two promising research and application frameworks of UAV communications, namely UAV-assisted wireless communications and cellular-connected UAVs, where UAVs are integrated into the network as new aerial communication platforms and users, respectively. Furthermore, we point out promising directions for future research.

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

Cybersecurity challenges in vehicular communications

Time synchronization is a critical piece of infrastructure for any distributed system. Wireless sensor networks have emerged as an important and promising research area in the recent years. Time synchronization is important for many sensor network applications that require very precise mapping of gathered sensor data with the time of the events, for example, in tracking and vehicular surveillance. It also plays an important role in energy conservation in MAC layer protocols. The paper studies different existing methods, protocols, significant time parameters (clock drift, clock speed, synchronization errors, and topologies) to achieve accurate synchronization in a sensor network. The studied Synchronization protocols include conventional time sync protocols (RBS, Timing-sync Protocol for Sensor Networks -TPSN, FTSP), and other application specific approaches such as all node-based approach, a diffusion-based method and group sync approaches aiming at providing network-wide time. The goal for writing this paper is to study most common existing time synchronization approaches and stress the need of a new class of secure-time synchronization protocol that is scalable, topology independent, fast convergent, energy efficient, less latent and less application dependent in a heterogeneous hostile environment. Our survey provides a valuable framework by which protocol designers can compare new and existing synchronization protocols from various metric discussed in the paper. So, we are hopeful that this paper will serve a complete one-stop investigation to study the characteristics of existing time synchronization protocols and its implementation mechanism in a Sensor network environment.

Time synchronization in wireless sensor networks: a survey

Unmanned aerial vehicles (UAVs) have significantly disrupted the aviation industry. As technology and policy continue to develop, this disruption is only going to increase in magnitude. A specific ...

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UAV swarm communication and control architectures: a review

Electrical grids are highly complex and dynamic systems that can be unreliable, insecure, and inefficient in serving end consumers The promise of Smart Grids lies in the architecting and developing of intelligent distributed and networked systems for automated monitoring and controlling of the grid to improve performance We have designed an agent-oriented architecture for a simulation which can help in understanding Smart Grid issues and in identifying ways to improve the electrical grid We focus primarily on the self-healing problem, which concerns methodologies for activating control solutions to take preventative actions or to handle problems after they occur We present software design issues that must be considered in producing a system that is flexible, adaptable and scalable Agent-based systems provide a paradigm for conceptualizing, designing, and implementing software systems Agents are sophisticated computer programs that can act autonomously and communicate with each other across open and distributed environments We present design issues that are appropriate in developing a Multi-agent System (MAS) for the grid Our MAS is implemented in the Java Agent Development Framework (JADE) Our Smart Grid Simulation uses many types of agents to acquire and monitor data, support decision making, and represent devices, controls, alternative power sources, the environment, management functions, and user interfaces

Agent-Oriented Designs for a Self Healing Smart Grid

The utility of unmanned aerial vehicles (UAVs) has significantly disrupted aviation-related industries. As technology and policy continue to develop, this disruption is likely to continue and become even larger in magnitude. A specific technology poised to disrupt industry is UAV swarm. UAV swarm has the potential to distribute tasks and coordinate operation of many drones with little to no operator intervention. This paper surveys literature regarding UAV swarm and proposes a swarm architecture that will allow for higher levels of swarm autonomy and reliability by utilizing cellular mobile network infrastructure. Additionally, this paper chronicles initial testbed development to meet this proposed architecture. Specific development of higher levels of autonomous swarms with UAV-to-UAV communication and coordination ability is central to advancing the utility of UAV swarms. The use of cellular mobile framework alleviates many limiting factors for UAVs including range of communication, networking challenges, size-weight-and-power (SWaP) considerations, while leveraging a robust and reliable infrastructure for machine to machine (M2M) communication proposed by 5G systems.

Prakash Ranganathan

Papers

Cybersecurity challenges in vehicular communications

Time synchronization in wireless sensor networks: a survey

UAV swarm communication and control architectures: a review

Agent-Oriented Designs for a Self Healing Smart Grid

Notice of Removal: A Review and Future Directions of UAV Swarm Communication Architectures