Results 1 -
9 of
9
Distributed internet-based load altering attacks against smart power grids
- IEEE Transactions on Smart Grid
, 2011
"... Abstract—With the increase in use of information technology in advanced demand side management and given the growth in power consumption in the computation and communications sectors, a new class of cyber-intrusion plans is emerging that aims to alter the load through the Internet and by means of au ..."
Abstract
-
Cited by 14 (2 self)
- Add to MetaCart
(Show Context)
Abstract—With the increase in use of information technology in advanced demand side management and given the growth in power consumption in the computation and communications sectors, a new class of cyber-intrusion plans is emerging that aims to alter the load through the Internet and by means of automatic and distributed software intruding agents. These attacks work by compromising direct load control command signals, demand side management price signals, or cloud computation load distribution algorithms to affect the load at the most crucial locations in the grid in order to cause circuite overflow or other malfunctions and damage the power system equipments. To gain insights into these less-examined yet important intrusion strategies, in this paper, we identify a variety of practical loads that can be volnurable to Internet-based load altering attacks. In addition, we overview a collection of defence mechanisms that can help in blocking these attacks or minimizing the damage caused by them. Our simulation results based on the standard setting in the IEEE 24-bus Reliability Test System show that our proposed cost-efficent load protection strategy can significantly reduce the cost of load protection while it guarantees that no Internet-based load altering attack may overload the power distribution system.
Cutting Down Electricity Cost in Internet Data Centers by Using Energy Storage
- In Proc. of GLOBECOM
, 2011
"... Abstract—Electricity consumption comprises a significant frac-tion of total operating cost in data centers. System operators are required to reduce electricity bill as much as possible. In this paper, we consider utilizing available energy storage capability in data centers to reduce electricity bil ..."
Abstract
-
Cited by 8 (1 self)
- Add to MetaCart
(Show Context)
Abstract—Electricity consumption comprises a significant frac-tion of total operating cost in data centers. System operators are required to reduce electricity bill as much as possible. In this paper, we consider utilizing available energy storage capability in data centers to reduce electricity bill under real-time electricity market. Laypunov optimization technique is applied to design an algorithm that achieves an explicit tradeoff between cost saving and energy storage capacity. As far as we know, our work is the first to explore the problem of electricity cost saving using energy storage in multiple data centers by considering both time-diversity and location-diversity of electricity price. Index Terms—Cloud computing, electricity cost, data center, energy storage, Laypunov optimization I.
Opportunities and challenges for data center demand response
- In IGCC
, 2014
"... Abstract-This paper surveys the opportunities and challenges in an emerging area of research that has the potential to significantly ease the incorporation of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at ..."
Abstract
-
Cited by 6 (0 self)
- Add to MetaCart
(Show Context)
Abstract-This paper surveys the opportunities and challenges in an emerging area of research that has the potential to significantly ease the incorporation of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data centers and demand response in the smart grid. As such, the literature related to data center demand response is sprinkled across multiple areas and worked on by diverse groups. Our goal in this survey is to demonstrate the potential of the field while also summarizing the progress that has been made and the challenges that remain.
A Survey on Geographic Load Balancing Based Data Center
- Power Management in the Smart Grid Environment,” IEEE Communications Surveys and Tutorials
"... Abstract—Power management is becoming an increasingly important issue for Internet services supported by multiple geo-distributed data centers. These data center’s energy consumptions and costs are becoming unacceptably high, and placing a heavy burden on both energy resources and the environment. E ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
(Show Context)
Abstract—Power management is becoming an increasingly important issue for Internet services supported by multiple geo-distributed data centers. These data center’s energy consumptions and costs are becoming unacceptably high, and placing a heavy burden on both energy resources and the environment. Emerging smart grid provides a feasible way for dynamic and efficient power management of data centers. Various power management methodologies based on geographic load balancing (GLB) have recently been proposed to effectively utilize several features of smart grid. In this paper, we summarize the motivations, current state of the art, approaches and techniques proposed in the recent research works in this discipline. In all of these works, many perspectives of power management have been addressed using various computer science principles. We specifically elaborate on how researchers are exploiting mathematical tools to address these perspectives. Finally, we point out subject matters that need more attentions from the research community and provide our vision on possible future works along this direction.
Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks
"... Abstract Datacenters are one of the important global energy consumers and carbon producers. However, their tight service level requirements prevent easy integration with highly variable renewable energy sources. Short-term green energy prediction can mitigate this variability. In this work, we first ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
(Show Context)
Abstract Datacenters are one of the important global energy consumers and carbon producers. However, their tight service level requirements prevent easy integration with highly variable renewable energy sources. Short-term green energy prediction can mitigate this variability. In this work, we first explore the existing short-term solar and wind energy prediction methods, and then leverage prediction to allo-cate and migrate workloads across geographically distributed datacenters to reduce brown energy consumption costs. Unlike previous works, we also study the impact of wide area networks (WAN) on datacenters, and investigate the use of green en-ergy prediction to power WANs. Finally, we present two different studies connect-ing datacenters and WANs: the case where datacenter operators own and manage their WAN and the case where datacenters lease networks from WAN providers. The results show that prediction enables up to 90 % green energy utilization, a 3x improvement over the existing methods. The cost minimization algorithm reduces expenses by up to 16 % and increases performance by 27 % when migrating work-loads across datacenters. Furthermore, the savings increase up to 30 % compared with no migration when servers are made energy-proportional. Finally, in the case of leasing the WAN, energy proportionality in routers can in-crease the profit of network providers by 1.6x.
Simulation Modelling Practice and Theory xxx (2013) xxx–xxx Contents lists available at SciVerse ScienceDirect Simulation Modelling Practice and Theory
"... journal homepage: www.elsevier.com/locate/simpat A survey of mathematical models, simulation approaches and testbeds used for research in cloud computing ..."
Abstract
- Add to MetaCart
journal homepage: www.elsevier.com/locate/simpat A survey of mathematical models, simulation approaches and testbeds used for research in cloud computing
Coordination of Cloud Computing and Smart Power
"... Abstract—The emergence of cloud computing has established a trend towards building massive, energy-hungry, and geograph-ically distributed data centers. Due to their enormous energy consumption, data centers are expected to have major impact on the electric grid by significantly increasing the load ..."
Abstract
- Add to MetaCart
(Show Context)
Abstract—The emergence of cloud computing has established a trend towards building massive, energy-hungry, and geograph-ically distributed data centers. Due to their enormous energy consumption, data centers are expected to have major impact on the electric grid by significantly increasing the load at locations where they are built. However, data centers and cloud computing also provide opportunities to help the grid with respect to robustness and load balancing. To gain insights into these opportunities, we formulate the service request routing problem in cloud computing jointly with the power flow analysis in smart grid and explain how these problems can be related. Simulation results based on the standard setting in the IEEE 24-bus Reliability Test System show that a grid-aware service request routing design in cloud computing can significantly help in load balancing in the electric grid and making the grid more reliable and more robust with respect to link breakage and load demand variations. I.
SMART GRID COST OPTIMIZATION USING GENETIC ALGORITHM
"... Formerly, energy had been inexpensive and management of energy was efficient and was limited to elementary considerations. In the current scenario, due to a rapid increase in demand, complexity of the electrical network, probability of contingency and electricity cost have equally increased. In the ..."
Abstract
- Add to MetaCart
(Show Context)
Formerly, energy had been inexpensive and management of energy was efficient and was limited to elementary considerations. In the current scenario, due to a rapid increase in demand, complexity of the electrical network, probability of contingency and electricity cost have equally increased. In the recent past, Smart Grids are proven to be the best way to minimize these problems in an easier and smart way. Smart grid is defined as an electric network which has information technology fused to it. This paper proposes a way to reduce the total electricity cost in a smart grid using Genetic Algorithm. The system considered has renewable energy and battery banks apart from the grid to meet the demand. Short term time averaged electricity cost is formulated as an objective for optimization by GA with discharge of battery, energy from the grid to charge battery and meet load etc. as decision variables. The optimization problem is run for a 24 hours data of renewable input, real-time electricity price and load using MATLAB software; and the obtained results are furnished.
A Comprehensive Approach to Reduce the Energy Cost of Network of Datacenters
"... Abstract—Several studies have proposed job migration over the wide area network (WAN) to reduce the energy of networks of datacenters by taking advantage of different electricity prices and load demands. Each study focuses on only a small subset of network parameters and thus their results may have ..."
Abstract
- Add to MetaCart
Abstract—Several studies have proposed job migration over the wide area network (WAN) to reduce the energy of networks of datacenters by taking advantage of different electricity prices and load demands. Each study focuses on only a small subset of network parameters and thus their results may have large errors. For example, datacenters usually have long-term power contracts instead of paying market prices. However, previous work neglects these contracts, thus overestimating the energy savings by 2.3x. We present a comprehensive approach to minimize the energy cost of networks of datacenters by modeling performance of the workloads, power contracts, local renewable energy sources, different routing options for WAN and future router technologies. Our method can reduce the energy cost of datacenters by up to 28%, while reducing the error in the energy cost estimation by 2.6x. Keywords- Datacenter, energy, green energy, job migration I.
