Software-defined networking for ubiquitous healthcare service delivery

The growth of the mobile, portable devices and the server-to-server communication through cloud computing increase the network traffic. The dependence of the ubiquitous healthcare service delivery on the network connectivity creates failures that may interrupt or delay the treatment plan with adverse effects in patients’ quality of life even leading to mortality. In the present work, we propose the incorporation of Software Defined Networking (SDN) features in the healthcare domain in order to provide the appropriate bandwidth and guarantee the accurate real time medical data transmission independently of the connectivity of the ISP provider. The SDN controller monitors the network traffic and specifies how traffic should be routed providing load balancing, lower delays and better performance. Finally, the proposed healthcare architecture addresses the SDN scalability challenge by incorporating the logically centralized control plane using multiple distributed controllers. A 2-tier hierarchical overlay is formed among SDN controllers following the principles of peer-to-peer networking

Fog computing security: a review of current applications and security solutions

Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the Fog platform highly suitable for time and location-sensitive applications. For example, Internet of Things (IoT) devices are required to quickly process a large amount of data. This wide range of functionality driven applications intensifies many security issues regarding data, virtualization, segregation, network, malware and monitoring. This paper surveys existing literature on Fog computing applications to identify common security gaps. Similar technologies like Edge computing, Cloudlets and Micro-data centres have also been included to provide a holistic review process. The majority of Fog applications are motivated by the desire for functionality and end-user requirements, while the security aspects are often ignored or considered as an afterthought. This paper also determines the impact of those security issues and possible solutions, providing future security-relevant directions to those responsible for designing, developing, and maintaining Fog systems

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

A Survey on the Security and the Evolution of Osmotic and Catalytic Computing for 5G Networks

The 5G networks have the capability to provide high compatibility for the new applications, industries, and business models. These networks can tremendously improve the quality of life by enabling various use cases that require high data-rate, low latency, and continuous connectivity for applications pertaining to eHealth, automatic vehicles, smart cities, smart grid, and the Internet of Things (IoT). However, these applications need secure servicing as well as resource policing for effective network formations. There have been a lot of studies, which emphasized the security aspects of 5G networks while focusing only on the adaptability features of these networks. However, there is a gap in the literature which particularly needs to follow recent computing paradigms as alternative mechanisms for the enhancement of security. To cover this, a detailed description of the security for the 5G networks is presented in this article along with the discussions on the evolution of osmotic and catalytic computing-based security modules. The taxonomy on the basis of security requirements is presented, which also includes the comparison of the existing state-of-the-art solutions. This article also provides a security model, "CATMOSIS", which idealizes the incorporation of security features on the basis of catalytic and osmotic computing in the 5G networks. Finally, various security challenges and open issues are discussed to emphasize the works to follow in this direction of research.Comment: 34 pages, 7 tables, 7 figures, Published In 5G Enabled Secure Wireless Networks, pp. 69-102. Springer, Cham, 201

PPS-ADS: A Framework for Privacy-Preserved and Secured Distributed System Architecture for Handling Big Data

The exponential expansion of Big Data in 7V’s (velocity, variety, veracity, value, variability and visualization) brings forth new challenges to security, reliability, availability and privacy of these data sets. Traditional security techniques and algorithms fail to complement this gigantic big data. This paper aims to improve the recently proposed Atrain Distributed System (ADS) by incorporating new features which will cater to the end-to-end availability and security aspects of the big data in the distributed system. The paper also integrates the concept of Software Defined Networking (SDN) in ADS to effectively control and manage the routing of the data item in the ADS. The storage of data items in the ADS is done on the basis of the type of data (structured or unstructured), the capacity of the distributed system (or coach) and the distance of coach from the pilot computer (PC). In order to maintain the consistency of data and to eradicate the possible loss of data, the concept of “forward positive” and “backward positive” acknowledgment is proposed. Furthermore, we have incorporated “Twofish” cryptographic technique to encrypt the big data in the ADS. Issues like “data ownership”, “data security, “data privacy” and data reliability” are pivotal while handling the big data. The current paper presents a framework for a privacy-preserved architecture for handling the big data in an effective manner

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa