A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

What is a disaster

Summary
The Internet of Things (IoT) is a new technology that is growing rapidly in the field of telecommunications and especially in the modern field of wireless telecommunications. The main goal of the interaction and cooperation between things and objects sent through the wireless networks is to fulfill the objective set to them as a combined entity. In addition, based on the technology of wireless networks, both the technologies of Mobile Cloud Computing (MCC) and IoT develop rapidly. In this paper, we combine the two aforementioned technologies (i.e., MCC and IoT) with the technology of the Big Data in order to examine the common features and tο discover which of the MCC and IoT benefits improve the use of the Big Data applications. Finally, we present the contribution of MCC and IoT individually to the technology of Big Data. Copyright © 2016 John Wiley & Sons, Ltd.

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

Formal verification approaches and standards in the cloud computing

The past few decades have witnessed an intensive research on optical character recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also reported on OCR efforts for various Indian scripts, like Devanagari, Bangla, Oriya, Tamil, Telugu, Malayalam, Kannada, Gurmukhi, Gujarati, etc. In this paper, we present a review of OCR work on Indian scripts, mainly on Bangla and Devanagari—the two most popular scripts in India. We have summarized most of the published papers on this topic and have also analysed the various methodologies and their reported results. Future directions of research in OCR for Indian scripts have been also given.

/pdf/a-survey-on-optical-character-recognition-for-bangla-and-3tmybx9xa2.pdf

A survey on optical character recognition for Bangla and Devanagari scripts

Human activity recognition primarily targets the identification of individual/group activities from acquired data, which can be captured commonly using smartphone based sensory units. Existing sensor based human activity recognition, including smartphone based activity recognition, has suffered from efficient performances to accurately recognize physical activities. In this paper, an efficient human activity recognition system, based on the new simplified convolutional neural network framework, is proposed. The proposed system also improves the overall recognition accuracy of human activities given as one-dimensional time-series dataset based on accelerometers and gyroscopes of smartphones. In particular, the proposed system accurately recognizes six types of physical activities, viz. walk, walk-upstairs, walk-downstairs, sit, stand and lay. The proposed system has been thoroughly experimented to show that its overall recognition accuracy increases to as high as 93.926%, with significant improvement in training time and testing time performances, which reach to a minimum of 3.4274 seconds and 372.6 milliseconds respectively. Consequently, the proposed system achieves time bound performances of accurate activity recognition, thereby advocating many societal benefits including disaster management.

Efficient Smartphone-Based Human Activity Recognition Using Convolutional Neural Network

Tuple Space based Mobile Middleware (TSMM), a new genre of mobile middleware, is developed to tackle emerging dynamics in underlying infrastructure. It uses tuple space model to coordinate interactions between different active components (agents) of supported applications. This paper focusses on a primary design issue of tuple space model, viz. tuple-antituple structure, which specifies arities and nature of arrangements of constituent fields of tuples and antituples. This factor not only affects application design, but also impacts simplicity, flexibility, scalability and performance of TSMM. Broadly, two types of arrangements are possible: ordered (where arity and arrangement of fields are predefined), and unordered (where none of them are predefined). Ordered structure lacks flexibility and restricts the design of TSMM and its applications. Unordered structure removes these drawbacks, but degrades TSMM's performance and scalability, as additional creation and lookup overheads are introduced here. Among the existing TSMM, LIMONE incorporates unordered tuple-antituple structure. In this paper, we modify LIMONE's tuple-antituple structure for improving its performance and scalability. Both original and modified models are analyzed and experimented to show the improvements.

On performance improvement issues in unordered Tuple Space based Mobile Middleware

In this paper, we propose an application layer based modified weight-throwing protocol for the distributed termination detection problem in a purely mobile distributed environment with no static hosts. The mobile hosts are considered with limited functionality. We discuss the effect of mobility on the proposed algorithm and analyze it.

A New Termination Detection Protocol for Mobile Distributed Systems

Tuple Space based Mobile Middleware (TSMM) is developed to tackle emerging dynamics in underlying infrastructure. Its coordination medium, viz. tuple space model, has multiple inherent decoupled behaviors to coordinate interactions between different agents of supported applications. This paper focuses on one such decoupling quality, synchronization decoupling, by which agents are decoupled from their invoked primitives. This decoupling ability is accomplished by including reactivity in tuple space model. Reactive tuple space model also enables development of robust and flexible applications for TSMM. However, in existing TSMM, this decoupling behavior has not been fully attained, as reactions are themselves coupled with invoked primitives, leading to additional network and processing overheads. This paper proposes an improved reactive tuple space model for TSMM with enhanced decoupling behavior of reactions to achieve robustness for supported applications. Proposed tuple space model is also formally modeled and verified by notation and proof logic of UNITY model.

Modeling an Enhanced Tuple Space Based Mobile Middleware in UNITY

Mobile cloud computing extends the existing facility of cloud computing paradigm to different mobile applications executing in mobile/portable devices of end users. It caters these applications with the support of existing cloud services, thereby helping them to overcome the inherent limitations of mobile/portable devices. However, existing cloud services in mobile cloud architecture get tightly coupled with these applications, which is highly undesirable in dynamic and unreliable mobile cloud computing. A new mobile cloud architecture, where interactions between mobile applications and existing cloud services are decoupled in nature, is proposed in this paper. Tuple space model is used for decoupling these interactions in proposed architecture, which improves flexibility and efficiency of mobile cloud computing. This paper also suggests an approach of formalizing proposed architecture in order to appropriately analyze its flexibility in decoupling mobile applications from their leased cloud services. Formalization is carried out using Mobile UNITY.

Suddhasil De

Papers

Efficient Smartphone-Based Human Activity Recognition Using Convolutional Neural Network

On performance improvement issues in unordered Tuple Space based Mobile Middleware

A New Termination Detection Protocol for Mobile Distributed Systems

Modeling an Enhanced Tuple Space Based Mobile Middleware in UNITY

On the Notion of Decoupling in Mobile Cloud Computing