Byung Kyu Choi

Endpoint admission control: network based approach

Proposes a network-based endpoint admission control system for scalable QoS-guaranteed real-time communication services. This system is based on a sink tree-based resource management strategy and is particularly well-suited for differentiated services-based architectures. By performing the admission decision at the endpoints, the flow setup latency and the signaling overhead are kept to a minimum. In addition, the proposed system integrates routing and resource reservation along the routes, and therefore displays higher admission probability and better link resource utilization. This approach achieves a low overall admission control overhead because much of the delay computation is done during system configuration, and so resources can effectively be pre-allocated before run time. We investigate a number of resource-sharing approaches that allow resources to be efficiently re-allocated at run time with minimized additional overhead. We provide simulation experiments that illustrate the benefits of using sink tree-based resource management for resource pre-allocation and for routing, both with and without resource sharing.

Scalable QoS guaranteed communication services for real-time applications

We propose an approach to flow-unaware admission control which is a combination with an aggregate packet forwarding scheme, improving scalability of networks while guaranteeing end-to-end deadlines for real-time applications. We achieve this by using an off-line delay computation and verification step, which allows to reduce the overhead at admission control while keeping admission probability and resource utilization high. Our evaluation data show that our systems admission probabilities are very close to those of significantly more expensive flow-aware approaches. At the same time, the admission control overhead during flow establishment is very low. Our results therefore support the claim from the DS architecture literature that scalability can be achieved through flow aggregation without sacrificing resource utilization and with significant reduction in run time overhead.

MuON: epidemic based mutual anonymity

A mutually anonymous service hides the identity of a client from the service provider and vice-versa. Providing mutual anonymity usually requires a large number of participants. While peer-to-peer (P2P) networks are capable of recruiting a large number of participants, reliable anonymous communication in these architectures, with low bandwidth usage, still needs further investigation. This paper presents MuON, a protocol to achieve mutual anonymity in unstructured P2P networks. MuON leverages epidemic-style data dissemination to deal with the high churn (changes in system membership) characteristic of unstructured P2P networks. The results from our security analysis and simulation show that MuON provides mutual anonymity over unstructured P2P networks while maintaining predictable latencies, high reliability, and low communication overhead

Utilization-Based Admission Control for Scalable Real-Time Communication

We propose a utilization-based schedulability and admission control mechanism for distributed systems with workload aggregation to achieve scalability. We use the differentiated services (diffserv) architecture to describe and illustrate our approach. Scalability of admission control is achieved by determining off-line safe levels of server utilization. Scalability during the connection lifetimes is provided by the aggregation mechanisms (for example, class-based scheduling) provided by the diffserv architecture. Our evaluations show that our systems admission probabilities are very close to those of significantly more expensive approaches, which do not allow for workload aggregation. At the same time, admission control overhead during flow establishment is very low.

Fast software component migration for applications survivability in distributed real-time systems

In this paper we propose and evaluate a methodology for run-time fast software component migration for application survivability in distributed real-time systems. For fast migration we focus on the two dominant factors; lightweight migration and proactive resource discovery. The former is to minimize the absolute amount of time required for migration and the latter is to provide a destination host information at the time of migration decision. The run-time software component is implemented as Java object whose class is defined by extending the unicast remote server class. The proactive resource discovery consists of Community protocol and associated algorithms. These two ideas have been implemented as a middleware that also provides a real-time job scheduler in JVM (Java Virtual Machine), and a naming server. Our analysis and simulation in a cluster computing environment show that the proactive resource discovery requires very low communication overhead while maintaining high effectiveness in finding available CPU resources. Our implementation and measurement show that run-time component migration based on our approach takes much less time compared to the approach based on reactive resource discovery

MuON: Epidemic based mutual anonymity in unstructured P2P networks

A mutual anonymity system enables communication between a client and a service provider without revealing their identities. In general, the anonymity guarantees made by the protocol are enhanced when a large number of participants are recruited into the anonymity system. Peer-to-peer (P2P) systems are able to attract a large number of nodes and hence are highly suitable for anonymity systems. However, the churn (changes in system membership) within P2P networks, poses a significant challenge for low-bandwidth reliable anonymous communication in these networks. This paper presents MuON, a protocol to achieve mutual anonymity in unstructured P2P networks. MuON leverages epidemic-style data dissemination to deal with churn. Simulation results and security analysis indicate that MuON provides mutual anonymity in networks with high churn, while maintaining predictable latencies, high reliability, and low communication overhead.

Efficient resource management for hard real-time communication over differentiated services architectures

We propose an efficient strategy for resource management for scalable QoS guaranteed real-time communication services. This strategy is based on sink trees, and is particularly well suited for differentiated-services based architectures. We first show that finding a set of sink-trees in a given network is NP-complete. Then we propose a heuristic algorithm that always efficiently produces a set of sink-trees for a given network. Sink-tree based resource management integrates routing and resource reservation along the routes, and therefore has a number of advantages over other resource management scheme, in terms of: admission probability, link resource utilization, flow set up latency, signaling overhead, and routing over-head. In this paper we show by simulation experiments that even for simple cases the sink-tree based approach shows excellent results in terms of admission probability.

Dynamic resource discovery for applications survivability in distributed real-time systems

We propose a new resource discovery protocol, REALTOR, which is based on a combination of pull-based and push-based resource information dissemination. REALTOR has been designed for real-time component-based distributed applications in very dynamic or adverse environments. REALTOR supports survivability and information assurance by allowing the migration of components to safe locations under emergencies like external attack, malfunction, or lack of resources. Simulation studies show that under normal and heavy load conditions REALTOR remains very effective in finding available resources with a reasonably low communication overhead. REALTOR: 1) effectively locates resources under highly dynamic conditions, 2) has an overhead that is system-size independent, and 3) works well in highly adverse environments. We evaluate the effectiveness of a REALTOR implementation as part of Agile Objects, an infrastructure for real-time capable, highly mobile Java components.

DIMPLE: DynamIc Membership ProtocoL for epidemic protocols

Epidemic protocols assume that information of a random set of nodes is provided at each protocol round. By definition, the random set needs to be chosen uniformly and randomly from the entire set to gossip with. Consequently, a node observes a different set of randomly chosen nodes at each different protocol round. Several proposals have addressed the issue of providing a different random set of nodes at each different round. In general, for large systems, this is done by creating a partial view of the entire membership at each node and exchanging part of the partial view among nodes. While many interesting properties of this approach have been found, investigation is needed to study the performance of this approach with practically high network churn. Without an action specifically designed for churn, shuffling would produce many dangling pointers in the partial view which point to an already left node. This in turn would significantly degrade the quality of epidemic protocols. The reason for the poor quality of the partial view is that the procedures of leave and join can take too long time to handle churn efficiently. To address this issue, an additional action of reinforcement and a new join procedure are proposed and evaluated in this paper. The reinforcement detects and removes dangling pointers at each shuffle more effectively, and the new join procedure accommodates a newly joining node remarkably fast. The subsequent simulations show that these ideas enhance the shuffling mechanism such that the system processes network churn much faster and the quality of the node degrees is significantly enhanced.

Edge-limited scalable QoS flow set-up

Although the Differentiated Services architecture supports scalable packet forwarding based on aggregate flows, the detailed procedure of Quality of Service (QoS) flow set-up within this architecture has not been well established. In this paper we explore the possibility of a scalable QoS flow set-up using a sink-tree paradigm. The paradigm initially constructs a sink tree at each egress edge router using network topology and bandwidth information provided by a QoS extended version of Open Shortest Path First (OSPF), which is a widely used link-state routing protocol. Our sink-tree paradigm dynamically reallocates network bandwidths online according to traffic demands. As a consequence, our paradigm easily supports QoS routing, resource allocation, and admission control at ingress edge routers without consulting core routers in a way that the QoS flow set-up time and overhead are minimized. Simulation results are very encouraging in that the proposed methodology requires significantly less communication overhead in setting up QoS flows compared to the traditional per-flow signaling-based methodology while still maintaining high resource utilization.