Stein Gjessing

Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach

Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.

Cognitive machine-to-machine communications: visions and potentials for the smart grid

Based upon cognitive radio technology, we propose a new Machine-to-Machine (M2M) communications paradigm, namely Cognitive M2M (CM2M) communication. We first motivate the use of cognitive radio technology in M2M communications from different point of views, including technical, applications, industry support, and standardization perspectives. Then, our CM2M network architecture and cognitive machine model are presented and the CM2M systems coexistence in TV white spaces is discussed. After that, a CM2M communications architecture for the smart grid is presented, for which we also propose an energy-efficiency driven spectrum discovery scheme. Numerical results demonstrate significant energy saving and the reliability in supporting data transmissions in the smart grid.

Fast IP Network Recovery Using Multiple Routing Configurations

As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence of routing protocols after a network failure becomes a growing problem. To assure fast recovery from link and node failures in IP networks, we present a new recovery scheme called Multiple Routing Configurations (MRC). MRC is based on keeping additional routing information in the routers, and allows packet forwarding to continue on an alternative output link immediately after the detection of a failure. Our proposed scheme guarantee s recovery in all single failure scenarios, using a single mechanism to handle both link and node failures, and without knowing the root cause of the failure. MRC is strictly connectionless, and assumes only destination based hop-by-hop forwarding. It can be implemented with only minor changes to existing solutions. In this paper we present MRC, and analyze its performance with respect to scalability, backup path lengths, and load distribution after a failure.

Cognitive radio based hierarchical communications infrastructure for smart grid

The current centrally controlled power grid is undergoing a drastic change in order to deal with increasingly diversified challenges, including environment and infrastructure. The next-generation power grid, known as the smart grid, will be realized with proactive usage of state-of-the-art technologies in the areas of sensing, communications, control, computing, and information technology. In a smart power grid, an efficient and reliable communication architecture plays a crucial role in improving efficiency, sustainability, and stability. In this article, we first identify the fundamental challenges in the data communications for the smart grid and introduce the ongoing standardization effort in the industry. Then we present an unprecedented cognitive radio based communications architecture for the smart grid, which is mainly motivated by the explosive data volume, diverse data traffic, and need for QoS support. The proposed architecture is decomposed into three subareas: cognitive home area network, cognitive neighborhood area network, and cognitive wide area network, depending on the service ranges and potential applications. Finally, we focus on dynamic spectrum access and sharing in each subarea. We also identify a very unique challenge in the smart grid, the necessity of joint resource management in the decomposed NAN and WAN geographic subareas in order to achieve network scale performance optimization. Illustrative results indicate that the joint NAN/WAN design is able to intelligently allocate spectra to support the communication requirements in the smart grid.

Toward cloud-based vehicular networks with efficient resource management

In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.

Distributed-directory scheme: scalable coherent interface

The scalable coherent interface (SCI), a local or extended computer backplane interface being defined by an IEEE standard project (P1596), is discussed. the interconnection is scalable, meaning that up to 64 K processor, memory, or I/O nodes can effectively interface to a shared SCI interconnection. The SCI sharing-list structures are described, and sharing-list addition and removal are examined. Optimizations being considered to improve the performance of large system configurations are discussed. Request combining, a useful feature of linked-list coherence, is described. SCIs optional extensions, including synchronization using a queued-on-lock bit, are considered.<<ETX>>

IEEE 802.17 resilient packet ring tutorial

IEEE Working Group 802.17 is standardizing a new ring topology network architecture, called the resilient packet ring, to be used mainly in metropolitan and wide area networks. This article presents a technology background, gives an overview, and explains some of the design choices behind RPR. Some major architectural features are illustrated and compared by showing performance evaluation results using the RPR simulator developed at Simula Research Laboratory using the OPNET modeler simulation environment.

Multiple routing configurations for fast IP network recovery

As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence of routing protocols after a network failure becomes a growing problem. To assure fast recovery from link and node failures in IP networks, we present a new recovery scheme called Multiple Routing Configurations (MRC). Our proposed scheme guarantees recovery in all single failure scenarios, using a single mechanism to handle both link and node failures, and without knowing the root cause of the failure. MRC is strictly connectionless, and assumes only destination based hop-by-hop forwarding. MRC is based on keeping additional routing information in the routers, and allows packet forwarding to continue on an alternative output link immediately after the detection of a failure. It can be implemented with only minor changes to existing solutions. In this paper we present MRC, and analyze its performance with respect to scalability, backup path lengths, and load distribution after a failure. We also show how an estimate of the traffic demands in the network can be used to improve the distribution of the recovered traffic, and thus reduce the chances of congestion when MRC is used.

Sensing-Performance Tradeoff in Cognitive Radio Enabled Smart Grid

Smart grid is widely considered to be the next generation of power grid, where power generation, management, transmission, distribution, and utilization are fully upgraded to improve agility, reliability, efficiency, security, economy, and environmental friendliness. Demand response management (DRM) is recognized as a control unit of the smart grid, with the attempt to balance the real-time load as well as to shift the peak-hour load. Communications are critical to the accuracy and optimality of DRM, and hence at the core of the control performance of the smart grid. In this paper, we introduce cognitive radio into the smart grid to improve the communication quality. By means of spectrum sensing and channel switching, smart meters can decide to transmit data on either an original unlicensed channel or an additional licensed channel, so as to reduce the communication outage. Considering the energy cost taxed by spectrum sensing together with the control performance degradation incurred by imperfect communications, we formulate the sensing-performance tradeoff problem between better control performance and lower communication cost, paving the way towards a green smart grid. The impact of the communication outage on the control performance of DRM is also analyzed, which reduces the profit of power provider and the social welfare of the smart grid, although it may not always decrease the profit of power consumer. By employing the energy detector, we prove that there exists a unique optimal sensing time which yields the maximum tradeoff revenue, under the constraint that the licensed channel is sufficiently protected. Numerical results are provided to validate our theoretical analysis.

Reducing Internet Latency: A Survey of Techniques and Their Merits

Latency is increasingly becoming a performance bottleneck for Internet Protocol (IP) networks, but historically, networks have been designed with aims of maximizing throughput and utilization. This paper offers a broad survey of techniques aimed at tackling latency in the literature up to August 2014, as well as their merits. A goal of this work is to be able to quantify and compare the merits of the different Internet latency reducing techniques, contrasting their gains in delay reduction versus the pain required to implement and deploy them. We found that classifying techniques according to the sources of delay they alleviate provided the best insight into the following issues: 1) The structural arrangement of a network, such as placement of servers and suboptimal routes, can contribute significantly to latency; 2) each interaction between communicating endpoints adds a Round Trip Time (RTT) to latency, particularly significant for short flows; 3) in addition to base propagation delay, several sources of delay accumulate along transmission paths, today intermittently dominated by queuing delays; 4) it takes time to sense and use available capacity, with overuse inflicting latency on other flows sharing the capacity; and 5) within end systems, delay sources include operating system buffering, head-of-line blocking, and hardware interaction. No single source of delay dominates in all cases, and many of these sources are spasmodic and highly variable. Solutions addressing these sources often both reduce the overall latency and make it more predictable.