Ryota Egashira

Molecular communication for nanomachines using intercellular calcium signaling

Molecular communication is engineered biological communication (e.g., cell-to-cell signaling) that allows nanomachines (e.g., engineered organisms, artificial devices) to communicate through chemical signals in an aqueous environment. This paper describes the design of a molecular communication system based on intercellular calcium signaling networks. This paper also describes possible functionalities (e.g., signal switching and aggregation) that may be achieved in such networks.

A design of a molecular communication system for nanomachines using molecular motors

Molecular communication is one solution for nano-scale communication between nanomachines. Nanomachines (e.g., biological molecules, artificial devices) represent small devices or components that perform computation, sensing, or actuation. Molecular communication provides a mechanism for one nanomachine to encode or decode information into molecules and to send information to another nanomachine. This paper describes a molecular motor communication system in terms of a high level architecture for molecular communication. We also briefly discuss current and future work in molecular communication

Distributed and adaptive discovery using preference

Distributed applications produce the need of locating distributed network objects (i.e., data, application or users) that meet a certain search criteria in a large-scale and dynamic network. We propose a discovery mechanism that is fully distributed (without any centralized entity) and adaptive to dynamic network environments. The proposed discovery mechanism allows query originators to return feedbacks that describe the degree of the preference for discovery results. The preference of query originators is utilized to guide subsequent queries in a distributed manner, enhancing efficiency of discovery and improving the quality of discovery results. Furthermore an effective use of the preference of query originators enables the proposed mechanism to adapt to dynamic environment changes. We investigate the efficiency and adaptability of the proposed discovery mechanisms through simulations.

Distributed service discovery using preference

Distributed collaborative applications will be widely used in a future large-scale and dynamic network. Such applications require the capability of locating distributed network objects that better match query originators criteria. In this paper, a discovery mechanism utilizing query originators preference is proposed in order to locate objects preferred by query originators. The proposed mechanism allows query originators to return feedbacks that describe the degree of the preference for discovered objects. The preference of query originators is utilized to guide subsequent queries in a distributed manner, enhancing efficiency of discovery. The preference of query originators is also utilized to adaptively change forwarding paths of queries corresponding to varying network environments. Extensive simulation work shows that the proposed mechanism is efficient and adaptive to dynamics of the peer-to-peer network environment where transient objects often join and leave

Market-Based Cooperative Resource Allocation for Overlay Networks

In recent years, the notion of service overlay networks has been proposed as a promising solution for providing end-to-end QoS without changing the current Internet architecture. A major issue in deploying service overlay networks is determining how to allocate resources (such as link bandwidth) on a substrate network to overlay networks, while satisfying the end-to-end QoS requirements of applications running on each overlay network. This paper introduces the Market-based Cooperative Resource Allocation (MaCRA) architecture that achieves fair and efficient resource allocation in a decentralized manner. In MaCRA, resources on a substrate network are priced, and each overlay network provider creates an overlay network on a minimum cost basis to meet its application QoS requirements. MaCRA also allows each overlay network provider to trade their current resources with other overlay network providers when resources on a substrate network are not available or expensive. Simulation results demonstrate that MaCRA achieves fairness and efficiency in allocating resources for overlay networks when compared to existing mechanisms.

Market-Based Resource Allocation for Service Overlay Networks

In recent years, service overlay networks have been proposed as a promising solution to provide end-to-end QoS without changing the current Internet architecture. In deploying service overlay networks, one major issue is how to efficiently allocate resources (e.g., link bandwidth) on a substrate network to each application with end-to-end QoS requirement. This paper proposes a novel decentralized architecture that achieves efficient resource allocation using a market mechanism. Resources on a substrate network are priced and each application provider aims to buy resources needed to satisfy its QoS requirement with minimum cost, which leads to globally efficient resource allocation. In order to further enhance efficiency in resource allocation, the proposed architecture enables trade of resources between applications. Trade of resources allows an application provider to buy resources from other application providers when resources on a substrate network are unavailable or expensive. Simulation results demonstrate the validity of the proposed architecture in improving efficiency of resource allocation.

Distributed discovery using preference for query hits

We consider peer-to-peer and distributed networks where a large number of objects (such as users, information and applications) are distributed and they move dynamically. In such a distributed network environment, the ability to discover objects that match given query criteria, such as a set of keywords, is highly desirable. We propose a discovery mechanism that is scalable, adaptable and robust to a dynamic network environment. The proposed discovery mechanism is fully distributed (without using any centralized entity in the network) and includes novel features that utilize information about the preference of the discovery originator in order to provide higher quality hits to discovery originators selectively, resulting in less traffic than an existing broadcast based discovery mechanism. Our study methodology of the proposed discovery mechanism involves extensive simulations that compared our discovery mechanism with the performance of an existing broadcast based discovery mechanism.