Renewable and Nonrenewable Energy Flow Resiliency for Day-to-Day Production and Consumption

Energy resilience is about ensuring a business and end-use consumers have a reliable,regular supply of energy and contingency measures in place in the event of a power failure,generating a source of power such as electricity for daily needs from an uninterrupted source of energy no matter either renewable or nonrenewable.Causes of resilience issues include power surges,weather,natural disasters,or man-made accidents,and even equipment failure.The human operational error can also be an issue for grid-power supply to go down and should be factored into resilience planning.As the energy landscape undergoes a radical transformation,from a world of large,centralized coal plants to a decentralized energy world made up of small-scale gas-fired production and renewables,the stability of electricity supply will begin to affect energy pricing.Businesses must plan for this change.The challenges that the growth of renewables brings to the grid in terms of intermittency mean that transmission and distribution costs consume an increasing proportion of bills.With progress in the technology of AI(Artificial Intelligence)integration of such progressive technology in recent decades,we are improving our resiliency of energy flow,so we prevent any unexpected interruption of this flow.Ensuring your business is energy resilient helps insulate against price increases or fluctuations in supply,becoming critical to maintaining operations and reducing commercial risk.In the form short TM(Technical Memorandum),this paper covers this issue.

Energy Driven by Internet of Things Analytics and Artificial Intelligence

Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.

Striping and Scheduling for Large Scale Multimedia Servers

When designing a multimedia server, several things must be decided: which scheduling scheme to adopt, how to allocate multimedia objects on storage devices, and the round length with which the streams will be serviced. Several problems in the designing of large-scale multimedia servers are addressed, with the following contributions: (1) a striping scheme is proposed that minimizes the number of seeks and hence maximizes the performance; (2) a simple and efficient mechanism is presented to find the optimal striping unit size as well as the optimal round length, which exploits both the characteristics of VBR streams and the situation of resources in the system; and (3) the characteristics and resource requirements of several scheduling schemes are investigated in order to obtain a clear indication as to which scheme shows the best performance in realtime multimedia servicing. Based on our analysis and experimental results, the CSCAN scheme outperforms the other schemes. It is believed that the results are of value in the design of effective large-scale multimedia servers. Keywords realtime multimedia - storage server - scheduling - data placement - buffer management - variable bit rate This work was supported in part by the University IT Research Center Project and Sunmoon University Research Project.Kyung-Oh Lee is an associate professor in the Faculty of Computer and Information Sciences, Sunmoon University, Korea. He received his B.S., M.S. and Ph.D. degrees in computer science from Seoul National University in 1989, 1994 and 1999, respectively. His current research interests include multimedia system, database, mobile communication. He is a member of KIPS (Korea Information Processing Society).Jungho-Ho Park is a professor in the Divisions of Computer and Information Sciences, Sunmoon University, Korea. He received his M.S. and Ph.D. degrees in computer science from Osaka University in 1987 and 1990, respectively. His current research interests include distributed algorithms, e-learning and electronic commerce. He is a director of KIPS (Korea Information Processing Society) and a vice president of KIPS-IT certification.Yoon-Young Park is an associate professor in the Faculty of Computer and Information Sciences, Sunmoon University, Korea. He received his M.S. and Ph.D. degrees in computer science from Seoul National University in 1985 and 1994, respectively. His current research interests include embedded systems and sensor networks. He is a member of KIPS (Korea Information Processing Society).