Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Fog/edge computing has been proposed to be integrated with Internet of Things (IoT) to enable computing services devices deployed at network edge, aiming to improve the user’s experience and resilience of the services in case of failures. With the advantage of distributed architecture and close to end-users, fog/edge computing can provide faster response and greater quality of service for IoT applications. Thus, fog/edge computing-based IoT becomes future infrastructure on IoT development. To develop fog/edge computing-based IoT infrastructure, the architecture, enabling techniques, and issues related to IoT should be investigated first, and then the integration of fog/edge computing and IoT should be explored. To this end, this paper conducts a comprehensive overview of IoT with respect to system architecture, enabling technologies, security and privacy issues, and present the integration of fog/edge computing and IoT, and applications. Particularly, this paper first explores the relationship between cyber-physical systems and IoT, both of which play important roles in realizing an intelligent cyber-physical world. Then, existing architectures, enabling technologies, and security and privacy issues in IoT are presented to enhance the understanding of the state of the art IoT development. To investigate the fog/edge computing-based IoT, this paper also investigate the relationship between IoT and fog/edge computing, and discuss issues in fog/edge computing-based IoT. Finally, several applications, including the smart grid, smart transportation, and smart cities, are presented to demonstrate how fog/edge computing-based IoT to be implemented in real-world applications.

A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications

Technological evolution of mobile user equipments (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. Suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud (CC). Nevertheless, this option introduces significant execution delay consisting in delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such delay is inconvenient and make the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: i) decision on computation offloading, ii) allocation of computing resource within the MEC, and iii) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Industry investment and research interest in edge computing, in which computing and storage nodes are placed at the Internet's edge in close proximity to mobile devices or sensors, have grown dramatically in recent years. This emerging technology promises to deliver highly responsive cloud services for mobile computing, scalability and privacy-policy enforcement for the Internet of Things, and the ability to mask transient cloud outages. The web extra at www.youtube.com/playlist?list=PLmrZVvFtthdP3fwHPy_4d61oDvQY_RBgS includes a five-video playlist demonstrating proof-of-concept implementations for three tasks: assembling 2D Lego models, freehand sketching, and playing Ping-Pong.

The Emergence of Edge Computing

Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies It elaborates MEC orchestration considering both individual services and a network of MEC platforms supporting mobility, bringing light into the different orchestration deployment options In addition, this paper analyzes the MEC reference architecture and main deployment scenarios, which offer multi-tenancy support for application developers, content providers, and third parties Finally, this paper overviews the current standardization activities and elaborates further on open research challenges

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On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Fog computing extends the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are 1) low latency and location awareness, 2) widespread geographical distribution, 3) mobility, 4) very large number of nodes, 5) predominant role of wireless access, 6) strong presence of streaming and real time applications, and 7) heterogeneity. In this chapter, the authors argue that the above characteristics make the Fog the appropriate platform for a number of critical internet of things (IoT) services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).

Fog Computing and Its Role in the Internet of Things

Higher-order thinking, known as higher order thinking skills (HOTS), is a conception of education reorganization based on learning taxonomy. Skills involving analysis, evaluation and synthesis are considered to be of higher order, requiring diverse learning and teaching methods than the customary learning of facts and concepts. HOTS involves the learning of complex judgmental skills such as critical thinking and problem solving. They are activated when individuals encounter unfamiliar problems, uncertainties, questions, or dilemmas. Successful application of the skills results in justifications, decisions, performances, and products that are valid within the context of existing knowledge that encourages continued growth in other intellectual skills. The major difficulty in attaining HOTS among engineering students is that we still pursue the traditional approach of teacher-centered classroom where the teacher is an active transmitter and the students are passive recipients. To achieve HOTS among engineering students we establish an Active Learning Environment (ALE) with the effective usage of Information and communication technologies (ICT). Active learning is embodied in a learning environment where the teachers and students are actively engaged with the content through discussions, problem-solving, critical thinking, or a multitude of activities that encourage interaction among learners, instructors and the material. Supporting to active learning, the ICT usage lends itself to more student-centered learning. This paper demonstrates the strategies to achieve HOTS through various ALE strategies like Role Play, Jigsaw, Brainstorming, debate, Mind map etc for Concept Understanding and Group assignments, combined mini projects, Discussion on Topics, Quiz, and Puzzles for Concept Applying. We have applied various learning strategies and assessed the student outcomes. HOTS is achieved by developing applications or products, with improved inter personal skills and lifelong learning skills. The evidence for the effectiveness of ALE among engineering students is showed by great improvement in their academic result, placement record and research interests

Active Learning Environment for Achieving Higher-Order Thinking Skills in Engineering Education

With the world getting busier and health of the people is at stake, we proposed an innovative system named The Smart Chair new model of Health Monitoring system for telemedicine developed based on sensor technologies and Security. It assures health care services for people anywhere and anytime. The main objective of this project is to design and develop health monitoring system that can be observed by the doctor in real time as well as check history of patient's medical data via internet with an indication in case of abnormalities. The whole patient monitoring system is embedded to a chair where we can make the patient to sit down to read vital signs. The smart chair is capable of monitoring many physiological parameters (e.g. heart rate, blood pressure, pulse rate, body weight and body temperature). By using Smart chair, patients can be kept informed of their health condition, while medical staff is in remote area could receive data from those devices by using wifi and Gsm module and give patients suggestions in time. To save the life of person, time-sensitive medical data should be dealt as much as possible in Emergency Situations. Our Experiments will achieve data accuracy and sensitivity using fog. Fog computing is a recently approached technique which extends cloud computing to edge of network. The features in fog computing will be applied for time sensitive healthcare applications, which provide early notification of emergency situations to support smart decision making. During transmission of data to fog and cloud, attackers can steal the privacy of user's information become a major problem. Signcryption provides resource efficiency by performing data signing and encryption in a single step. We can solve this approach by sending encrypted data to cloud and fog with signcryption model. Users can retrieve data by decrypting with unsigncrytion model and getting results to mobile phones. The result proposed is that we design an Iot Based secure smart healthcare application.

Smart Chair-A Telemedicine Based Health Monitoring System

Agriculture is a sector that holds great promise to Indian economic growth. Production in rural Tamil Nadu is extremely low due to unscientific farming practices. The major challenges faced in Tamil Nadu agriculture are crop mapping, yield prediction, quality of food produced, irrigation management, variable rate fertilizer and pesticide due to lack of technical knowledge. Precision agriculture (PA) rules out all drawbacks of traditional agriculture. The main objective of the chapter is to enhance the productivity of rural Tamil Nadu in order to meet the growing demands of our country’s food supply chain An Integrated GIS and Knowledge-Based Automated Decision Support System for Precision Agriculture Using IoT

An Integrated GIS and Knowledge-Based Automated Decision Support System for Precision Agriculture Using IoT

Security and efficiency are the two contradictory objectives to be achieved in designing a secure key distribution protocol for a resource constraint wireless multicast IPv6 networks. In this study, the authors propose a polynomial-based multicast–unicast key distribution technique in which the group key should be securely distributed within the group with minimum overhead. The first dimension deals with the scalability problem, which is addressed by dividing the network into subgroups and each subgroup is managed by a subgroup manager. To achieve the efficiency, the transmission level is separated as unicast and multicast where unicast supports key generation and multicast uses polynomial P(x) for distributing group key without encryption. The second dimension aims at reducing communication, computation and storage costs of the proposed technique during join and leave. The third dimension focuses on the security aspects. To attain these three dimensions, the proposed technique has been implemented using a tree-based key management scheme and the performance is analysed with the existing schemes. From the observations, the performance of the proposed scheme is satisfactory in terms of communication, computation and storage costs as well as security.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-ifs.2015.0398

Raja Lavanya

Papers

Fog Computing and Its Role in the Internet of Things

Active Learning Environment for Achieving Higher-Order Thinking Skills in Engineering Education

Smart Chair-A Telemedicine Based Health Monitoring System

An Integrated GIS and Knowledge-Based Automated Decision Support System for Precision Agriculture Using IoT

Cost‐effective polynomial‐based multicast–unicast key distribution framework for secure group communication in IPv6 multicast networks