Random Linear Network Coding for 5G Mobile Video Delivery

An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

Utilization balancing algorithms for dynamic multicast scheduling problem in EON

Dynamic data transfer demands are often being a challenge for present communication networks, as they appear in unpredictable time and must be satisfied prior to deadline. Important kind are the multi-target demands occurring in task of replication, backup, database synchronization or file transferring in pear-to-pear networks. Optimal scheduling usually depends of the nature of transport network. In the paper we consider dynamic deadline-driven multicast scheduling problem over elastic optical network. We propose the method for improving link utilization by traffic balance for multicast demands. We present few heuristic algorithms and results of experiments, proving the benefits of balancing concept

A Survey of Research on Health Monitoring System using Mobile Cloud Computing by Home Node Base Station

This paper presents a E-health monitoring scheme based on HNB (home node base station) and mobile cloud computing. In this method, the health data of each user is captured by using sensors and sent to the corresponding devices (i.e desktop, laptop, mobile). From that device the health data is transferred to cloud under which the mobile device is registered. In HNB it is verified whether the user’s health is normal using a database stored inside the HNB. If any abnormality is detected it will shows some indication through some sounds or light. The E-health data are send to cloud for each 15 seconds. In cloud also the data is verified with the normal data and if any abnormalities found it will indicate by sending message to the corresponding healthcare center. The health data in the cloud are stored with high security and only authentic healthcare center can access the data. Based on health data the healthcare centre takes proper action to cure the patient. DOI: 10.17762/ijritcc2321-8169.15027

Coding for the Clouds: Coding Techniques for Enabling Security, Locality, and Availability in Distributed Storage Systems

Cloud systems have become the backbone of many applications such as multimedia streaming, e-commerce, and cluster computing. At the foundation of any cloud architecture lies a large-scale, distributed, data storage system. To accommodate the massive amount of data being stored on the cloud, these distributed storage systems (DSS) have been scaled to contain hundreds to thousands of nodes that are connected through a networking infrastructure. Such data-centers are usually built out of commodity components, which make failures the norm rather than the exception. In order to combat node failures, data is typically stored in a redundant fashion. Due to the exponential data growth rate, many DSS are beginning to resort to error control coding over conventional replication methods, as coding offers high storage space efficiency. This paradigm shift from replication to coding, along with the need to guarantee reliability, efficiency, and security in DSS, has created a new set of challenges and opportunities, opening up a new area of research. This thesis addresses several of these challenges and opportunities by broadly making the following contributions. (i) We design practically amenable, low-complexity coding schemes that guarantee security of cloud systems, ensure quick recovery from failures, and provide high availability for retrieving partial information; and (ii) We analyze fundamental performance limits and optimal trade-offs between the key performance metrics of these coding schemes. More specifically, we first consider the problem of achieving information-theoretic security in DSS against an eavesdropper that can observe a limited number of nodes. We present a framework that enables design of secure repair-efficient codes through a joint construction of inner and outer codes. Then, we consider a practically appealing notion of weakly secure coding, and construct coset codes that can weakly secure a wide class of regenerating codes that reduce the amount of data downloaded during node repair. Second, we consider the problem of meeting repair locality constraints, which specify the number of nodes participating in the repair process. We propose a notion of unequal locality, which enables different locality values for different nodes, ensuring quick recovery for nodes storing important data. We establish tight upper bounds on the minimum distance of linear codes with unequal locality, and present optimal code constructions. Next, we extend the notion of locality from the Hamming metric to the rank and subspace metrics, with the goal of designing codes for efficient data recovery from special types of correlated failures in DSS.We construct a family of locally recoverable rank-metric codes with optimal data recovery properties. Finally, we consider the problem of providing high availability, which is ensured by enabling node repair from multiple disjoint subsets of nodes of small size. We study codes with availability from a queuing-theoretical perspective by analyzing the average time necessary to download a block of data under the Poisson request arrival model when each node takes a random amount of time to fetch its contents. We compare the delay performance of the availability codes with several alternatives such as conventional erasure codes and replication schemes