Kyi Thar

Management of scalable video streaming in information centric networking

Ability of caching the contents is one of the most important feature of an Information Centric Networking (ICN) node. By managing the cache space intelligently we can improve network’s performance and increase users’ Quality of Experience (QoE). Moreover, scalable video streaming in ICN is envisioned to be very beneficial as well as a challenging issue. In this paper, we are proposing a mechanism for cache management and request forwarding policies for scalable video streaming in ICN. Our proposed cache decision policy ensures to cache the base layer of a scalable video near to the users, which is mandatory layer for decoding any SVC encoded video and is needed by all the users with any data-rate budget, and consequently cache the higher layers in the upper nodes in the CCN/ICN within a specific RTT range. Furthermore, our intelligent cache decision cover fairness by considering router’s cache capacity (inside the RTT range) and at the same time giving more priority to the nodes that are nearer to the users. A limited cooperative request forwarding mechanism, which is the part of our proposal, plays a role to improve users’ QoE by providing the popular requested contents quickly. We have intensively simulated our proposed cache management and request forwarding scheme. The simulation results show that our proposed solution outperforms the current cache management schemes and improve the cache utilization. Also our proposed scheme decrease the traffic flowing inside the network by eliminating the request flooding and providing the requested contents from the nearby location to the users. The proposed scheme provides video faster to the users, specially the mandatory base layer is provided very quickly to the users.

Efficient forwarding and popularity based caching for Content Centric Network

In Content Centric Network, caching and forwarding schemes can affect the performance of the whole network. The original caching and forwarding schemes are simple, but these schemes have some drawbacks. Firstly, the original caching scheme stores the same content on several neighboring routers along the request path. This redundant caching does not use the limited storage space available to the routers efficiently. Secondly, the original forwarding scheme in which the data requests are flooded to neighboring routers, also degrades the performance of the network. In this paper, we aim to solve the issues of using cache space of each router efficiently and forwarding the data requests effectively. In this proposal, we divided an Autonomous System (AS) in several groups of routers to cache the popular contents. Routers in a group cooperatively store the data and forward the Interest in order to increase the network performance. To improve the cache hit, the group of routers only store the popular contents and reduce the duplicate content without effecting the redundancy. We used Consistent Hashing to reduce overlapping contents and forward the request efficiently. The content popularity prediction algorithm assists the routers to store the popular contents that pass through them. Finally, we evaluated the performance of our proposed scheme by using a chunk level simulator.

Consistent Hashing Based Cooperative Caching and Forwarding in Content Centric Network

The original Content Centric Network (CCN) employs a simple caching scheme, Leave Copy Everywhere (LCE). However, this scheme is not efficient because cache redundancy reduces the storage capacity of the CCN network. In this paper, to resolve the issue of cache redundancy, we propose a cooperative caching decision and forwarding mechanism which is based on consistent hashing and virtual routers. We divide the Autonomous System (AS) into several groups of routers. The routers in the group cooperatively store the contents (Data) and also forward the requests (Interest) cooperatively in order to increase the caching performance of the CCN network. Finally, we evaluate our proposal by using a chunk-level simulator. The results show that the cache hit ratio of our proposed scheme is better than other proposed schemes.

Efficient parallel multi-path interest forwarding for mobile user in CCN

Internet traffic has been dramatically increasing due to development of IT technology and increase in the number of Internet service users. The existing TCP/IP network architecture has problems in terms of scalability and security. Therefore, to solve the traffic, scalability and security problems, novel network paradigms are being surveyed. Among these paradigms, Content-Centric Networking (CCN) is in spotlight and has shown great promise to handle these problems. We can avoid the bottleneck problem caused by many requests through this new paradigm. However, the transmission rate in CCN is a limitation when compared to the existing TCP/IP network. In order to enhance the transmission rate, we can adopt to multiple wireless interfaces available in the modern mobile device. Thus, we propose a scheme namely Parallel Multi-path Interest Forwarding Scheme in which it is possible to receive the contents more quickly compared to the existing CCN.

Network-assisted congestion control for information centric networking

Internet has grown very rapidly in the last couple of decades and still growing because of the expansion and utilization of various services and applications. Consequently, demand of delay and throughput sensitive services, like audio/video is also increasing. Information Centric Networking (ICN) is proposed as an architecture for the future Internet to meet the modern users and application requirements. In ICN users send requests (Interest Packets) for the Data they need. Interest packet is assigned a lifetime, which greatly affects the Quality of Experience (QoE) because user needs to resend the Interest, when the lifetime expires. Interest lifetime may be expired because of congestion, or Interest lifetime is shorter than the network delay, etc. Waiting for the expiration of an Interest lifetime to resend it is merely appropriate for best effort traffic, rather than services which require high throughput and are delay sensitive. In this paper, we propose Network-Assisted Congestion Control mechanism in ICN, which detects the congestion before it happens, and provides notification to downstream node. On reception of the notification, downstream node continuously reduces the traffic rate. However, when the downstream node fails to adjust the sending rate, the same procedure continues, until the sending node reduces the traffic rate through adjusting its congestion window. We have intensively evaluated our proposal by comparing it with similar proposal using ndnSIM. The experimental results show that our proposal achieves up to 59 percent performance improvement over other proposal in the literature.

Delivering Scalable Video Streaming in ICN enabled Long Term Evolution networks

Information Centric Networking (ICN) is envisioned to be the future Internet architecture and mobile access network e.g., Long Term Evolution (LTE), and 5G will be the major access networks. In this paper, we present a cache management and cooperative request forwarding schemes for Scalable Video Streaming (SVS) in Information Centric Networking (ICN) enabled mobile access networks. H.264/SVC encoded video is consisted a mandatory baselayer and multiple optional enhancement layers. Baselayer, which is enough to decode the video, though with the lowest quality, is needed by every user who want to watch the video while enhancement layers are used to improve the video quality. Only a subset of users download enhancement layers of the video. Therefore, caching the baselayer nearer to the users will increase their Quality of Experience. Furthermore, we introduce cooperative request forwarding for the baselayer of video to take more benefits from cache of neighboring base stations. We have intensively simulated our proposed schemes by extending chunk level simulator ccnsim which is developed over Omnet++. Our experimental results show that, cache hit rate can be improved significantly by adopting our proposed caching and Interest forwarding schemes.

A general and practical consolidation framework in CloudNFV

In cloud computing environment, power consumption is a critical factor for data centers. Effective power consumption control can improve significantly benefit for providers. In this paper, we derive from CloudNFV architecture, an open platform for implementing Network Functions Virtualization based on cloud computing and Software Defined Networking, to obtain an optimal power control strategy toward reducing CO2 emissions and maximize total utility of active resources. We propose a consolidation function for determining the On/Off strategy of each server and use live migration method to rearrange virtual machines in active resource components. The efficiency of our proposed model is demonstrated on the simulation environment.

Resources management in virtualized Information Centric Wireless Network

Information-Centric Networking (ICN) and Wireless Network Virtualization (WNV) are two emerging technologies for the next-generation network infrastructure. ICN provides the key technology to reduce the network traffic by caching the contents temporarily and aggregating the same content requests. WNV enables the resources sharing among Infrastructure Providers (InPs) and Mobile Virtual Network Operators (MVNOs), to reduce capital expenditures and operating expenses. Also, the network resource management becomes easier because of WNV. In this paper, we combine these two technologies to improve the performance of the network and the profit of the MVNOs. We formulate the optimization problem to solve the cache allocation problem and maximize the profit of MVNOs by controlling the usage of cache space, backhaul link, and radio resources. Finally, we validate our proposed scheme using a chunk-level simulator. The simulation results show that the proposed mechanism can improve the profit of MVNOs and users QoS.

Load-sharing based on relay-aided cooperative modeling in uplink two-tier cellular networks

In this paper, we study the relay-aided cooperative modeling that supports the load-sharing in uplink two-tier cellular networks. In our model, users in heavily loaded macrocell are shifted to lightly loaded smallcells with the assistance of relay users to mitigate Signal to Interference plus Noise Ratio (SINR) degradation problem in conventional direct handover. In order to promote relaying data of users which are selfish and rational, a trading exchange model based on Stackelberg game is proposed to optimize strategies of users. Relay users have pricing-based strategies on theirs power unit while shifted heavily loaded macrocell users have strategies to buy power levels of relay users. Optimal strategies are investigated using the backward induction analysis. Specifically, problems of NP-hard combinatorial optimization in relay user selections in the game are solved with a distributed algorithm based on matching theory. We intensively evaluate our proposed model by simulating it in Matlab which shows the efficiency of our proposal.