Masahiro Jibiki

A design of an ICN architecture within the framework of SDN

The core design principle of Information-Centric Networking (ICN) is in the name based routing that enables users to ask for a data object by its name and makes the network deliver it to users from a nearby cache if available. Software-Defined Networking (SDN) lowers the cost and complexity of network management by decoupling architecture from infrastructure, which promises the continuous evolution of the network architecture in a flexible manner. The synergy between ICN supporting efficient data dissemination as the norm and SDN providing flexible management framework enables the combination to be a fully controllable framework for efficient data dissemination. In this paper, we propose a design of an ICN architecture within the framework of SDN.

An efficient load-balancing mechanism for heterogeneous range-queriable cloud storage☆

Abstract The rising popularity of big data processing for semantically rich applications such as social networks and IoT (Internet of Things) has made the range-queriable cloud storage increasingly important. To support range queries, the data locality is preserved strictly, which makes the load balancing among nodes a challenging task. Currently, most of the range-queriable cloud storage adopts the combination of neighbor item exchange and neighbor migration methods, which incurs large overhead, and suffers from slow convergence. In this work, we present a novel virtual node based decentralized load-balancing method for range-queriable cloud storage. In our method, each physical node is partitioned into multiple virtual nodes, and all the virtual nodes are organized with range-queriable P2P network. Load balancing is conducted in both overlay level (between neighboring virtual nodes) without global knowledge and physical level (among physical nodes) with limited global knowledge. Both theoretical analysis and simulations show that our method can significantly reduce the overhead and shorten the convergence time.

Content Hunting for In-Network Cache: Design and Performance Analysis

In-network caching is a core technology for saving network resources and improving the response time in Information-/Content-Centric Networking (ICN/CCN). In an ordinary ICN/CCN, content name based routing is used to find cached content in the network. Although there have been several studies on effective and efficient cache retrieval from in-network caches, we propose a novel content hunting scheme, named Local Tree Hunting (LTH) from the point of view to approach the ideal performance. LTH hunts for the closest node to the request node among the nodes with disseminated cache content. It autonomously adjusts the hunting area by changing the size of the hunting tree depending on the degree to which the content has been disseminated through the network. The proposed scheme was verified in a performance analysis; it was shown to have almost the same level of performance as the case of finding the true closest node. System architecture and operations based on the proposed scheme are also described.

Hierarchy-aware skip graph for sensing resource discoveries on large-scale sensor overlay networks

The rapid development of sensor networks has made it possible to build a large-scale sensor overlay network by integrating separated sensor networks all over the world. In our previous research, we proposed to realize sensor overlay networks by connecting their gateways with skip graph (SG) overlay, which is distributed and self-organized, and supports retrieving sensing resources using their properties. Although this method has proven to be effective in some scenarios, the lack of proximity awareness of an SG makes it difficult to build large-scale sensor overlay systems efficiently. In this paper, we present the hierarchy-aware extension of SG (HSG), which uses a hierarchy-aware neighbor selection mechanism that integrates the hierarchy of the physical Internet into overlay construction and routing to improve latency and traffic locality. To construct an HSG efficiently under various network environments, we develop a hierarchy-aware sampling mechanism for nodes to identify better neighbors than SG. To verify and validate the feasibility of HSG as a building block of large-scale sensor overlay networks, we carried out extensive simulations in near practical scenarios, which were obtained by analyzing an Internet measurement dataset. We showed that HSG could improve the routing latency and locality significantly with little overhead.

A virtual replica node-based flash crowds alleviation method for sensor overlay networks

The rapid development of sensor networks has made it possible to build large-scale sensor overlay networks by integrating separated sensing resources. In our previous work, we employed a range queriable P2P (peer-to-peer) network, Skip Graph, as the overlay substrate of sensor overlay networks. Range queriable P2Ps such as Skip Graph enable retrieving sensing resources whose properties are within the specified range in an effective and scalable manner. A side effect of the range queriable property is that when flash crowds occur, it is likely that multiple nodes with successive keys/IDs will become hotspots at virtually the same time, which rarely happens in typical DHT (Distributed Hash Table)-based systems. In this work, we present a virtual replica node-based approach to protect sensor overlay networks from flash crowds. In the proposed approach, a hotspot node can request physically spare nodes located anywhere in the overlay to generate virtual nodes with its key and force the virtual replica nodes to join the overlay network as if they were normal nodes around the hotspot. The proposed method is effective for both single hotspot and hotspot zone scenarios. With theoretical analysis, simulations, and testbed experiments, we demonstrate that the proposed method is efficient, scalable and feasible.