Although IP Multicast offers efficient data delivery for large group communications, the most critical issue delaying widespread deployment of IP Multicast is the scalability of multicast forwarding state as the number of multicast groups increases. Sender-Initiated Multicast (SIM) was proposed as an alternative multicast forwarding scheme for small group communications with incremental deployment capability. The key feature of SIM is in its Preset mode with the automatic SIM tunneling function, which maintaining forwarding information states only on the branching routers. To demonstrate how SIM increases scalability with respect to the number of groups, in this paper we evaluate the proposed protocol both through simulations and real experiments. As from the network operator's point of view, the bandwidth consumption, memory requirements on state-and-signaling per session in routers, and the processing overhead are considered as evaluation parameters. Finally, we investigated the strategies for incremental deployment.

We examine delay performance of packets from constant bit rate (CBR) traffic whose delay is affected by non-real-time traffic. The delay performance is analyzed by solving the Σ Di/G/1 queue with vacations. Our analysis allows heterogeneous service time and heterogeneous interarrival time. Thus, we can get the impact of packet length of a stream on the delay time of other streams. We then give various numerical results for enterprise multimedia networks, which include voice, video and data communication services. From our quantitative evaluation, we conclude that packet length of video traffic has large influence on the delay time of voice traffic while voice traffic gives a little impact on the delay time of video traffic.

The Internet of Things (IoT) with its support for cyber-physical systems (CPS) will provide many latency-sensitive services that require very fast responses from network services. Mobile edge computing (MEC), one of the distributed computing models, is a promising component of the low-latency network architecture. In network architectures with MEC, mobile devices will offload heavy computing tasks to edge servers. There exist numbers of researches about low-latency network architecture with MEC. However, none of the existing researches simultaneously satisfy the followings: (1) guarantee the latency of computing tasks and (2) implement a real system. In this paper, we designed and implemented an MEC based network architecture that guarantees the latency of offloading tasks. More specifically, we first estimate the total latency including computing and communication ones at the centralized node called orchestrator. If the estimated value exceeds the latency requirement, the task will be rejected. We then evaluated its performance in terms of the blocking probability of the tasks. To analyze the results, we compared the performance between obtained from experiments and simulations. Based on the comparisons, we clarified that the computing latency estimation accuracy is a significant factor for this system.

Cloud computing, which enables users to enjoy various Internet services provided by data centers (DCs) at anytime and anywhere, has attracted much attention. In cloud computing, however, service quality degrades with user distance from the DC, which is unfair. In this study, we propose a bandwidth allocation scheme based on collectable information to improve fairness and link utilization in DC networks. We have confirmed the effectiveness of this approach through simulation evaluations.

In this research, we focused on fair bandwidth allocation on the Internet. The Internet provides communication services based on exchanged packets. The bandwidth available for each customer is often fluctuated. Fair bandwidth allocation is an important issue for ISPs to gain customer satisfaction. Static bandwidth allocation allows an exclusive bandwidth for specific traffic. Although it gives communications a QoS guarantee, it requires muany bandwidth resources as known as over-provisioning. In contrast with static control, dynamic control allocates bandwidth resources dynamically. It therefore utilizes bandwidth use more effectively. However, it needs control overhead in monitoring traffic and estimating the optimum allocation. The Transmission Control Protocol, or TCP is the dominant protocol on the Internet. It is also equipped with a traffic-rate-control mechanism. An adaptive bandwidth-allocation mechanism must control traffic that is under TCP control. Rapid feedback makes it possible to gain an advantage over TCP control. In this paper, we propose an Adaptive Bandwidth Allocation (ABA) mechanism as a feedback system for MPLS. Our proposal allows traffic to be regulated adaptively as its own weight value which can be assigned by administrators. The feedback bandwidth allocation in the previous work needs round-trip control delay in collecting network status along the communication path. We call this "round-trip feedback control." Our proposal, called "one-way feedback control," collects network status in half the time of roundtrip delay. We compare the performance of our one-way feedback-based mechanism and traditional round-trip feedback control under a simulation environment. We demonstrate the advantages of our rapid feedback control has using experimental results.

Although SDN provides desirable characteristics such as the manageability, flexibility and extensibility of the networks, it has a considerable disadvantage in its reliability due to its centralized architecture. To protect SDN-enabled networks under large-scale, unexpected link failures, we propose ResilientFlow that deploys distributed modules called Control Channel Maintenance Module (CCMM) for every switch and controllers. The CCMMs makes switches able to maintain their own control channels, which are core and fundamental part of SDN. In this paper, we design, implement, and evaluate the ResilientFlow.

In future mobile networks, new technologies will be needed to enable a mobile host to move across heterogeneous wireless access networks without disruption of the connection. In the past, many researchers have studied handover in such IP networks. In almost all cases, special network devices are needed to maintain the host's mobility. Moreover, a host cannot move across heterogeneous wireless access networks without degradation of the goodput for real-time communication, although a mobile host with multiple network interfaces can connect to multiple wireless access networks. For these reasons, we consider that a mobile host needs to manage seamless handover on an end-to-end basis. In this paper, we propose a multi-path transmission algorithm for end-to-end seamless handover. The main purpose of this algorithm is to improve the goodput during handover by sending the same packets along multiple paths, minimizing unnecessary consumption of network resources. We evaluate our algorithm through simulations and show that a mobile host gains a better goodput.

There have been several recent reports that botnet communication between bot-infected computers and Command and Control servers (C&C servers) using the Domain Name System (DNS) protocol has been used by many cyber attackers. In particular, botnet communication based on the DNS TXT record type has been observed in several kinds of botnet attack. Unfortunately, the DNS TXT record type has many forms of legitimate usage, such as hostname description. In this paper, in order to detect and block out botnet communication based on the DNS TXT record type, we first differentiate between legitimate and suspicious usages of the DNS TXT record type and then analyze real DNS TXT query data obtained from our campus network. We divide DNS queries sent out from an organization into three types — via-resolver, and indirect and direct outbound queries — and analyze the DNS TXT query data separately. We use a 99-day dataset for via-resolver DNS TXT queries and an 87-day dataset for indirect and direct outbound DNS TXT queries. The results of our analysis show that about 30%, 8% and 19% of DNS TXT queries in via-resolver, indirect and direct outbound queries, respectively, could be identified as suspicious DNS traffic. Based on our analysis, we also consider a comprehensive botnet detection system and have designed a prototype system.

Attaining extremely low latency service in 5G cellular networks is an important challenge in the communication research field. A higher QoS in the next-generation network could enable several unprecedented services, such as Tactile Internet, Augmented Reality, and Virtual Reality. However, these services will all need support from powerful computational resources provided through cloud computing. Unfortunately, the geolocation of cloud data centers could be insufficient to satisfy the latency aimed for in 5G networks. The physical distance between servers and users will sometimes be too great to enable quick reaction within the service time boundary. The problem of long latency resulting from long communication distances can be solved by Mobile Edge Computing (MEC), though, which places many servers along the edges of networks. MEC can provide shorter communication latency, but total latency consists of both the transmission and the processing times. Always selecting the closest edge server will lead to a longer computing latency in many cases, especially when there is a mass of users around particular edge servers. Therefore, the research studies the effects of both latencies. The communication latency is represented by hop count, and the computation latency is modeled by processor sharing (PS). An optimization model and selection policies are also proposed. Quantitative evaluations using simulations show that selecting a server according to the lowest total latency leads to the best performance, and permitting an over-latency barrier would further improve results.

Most of latency-sensitive mobile applications depend on computational resources provided by a cloud computing service. The problem of relying on cloud computing is that, sometimes, the physical locations of cloud servers are distant from mobile users and the communication latency is long. As a result, the concept of distributed cloud service, called mobile edge computing (MEC), is being introduced in the 5G network. However, MEC can reduce only the communication latency. The computing latency in MEC must also be considered to satisfy the required total latency of services. In this research, we study the impact of both latencies in MEC architecture with regard to latency-sensitive services. We also consider a centralized model, in which we use a controller to manage flows between users and mobile edge resources to analyze MEC in a practical architecture. Simulations show that the interval and controller latency trigger some blocking and error in the system. However, the permissive system which relaxes latency constraints and chooses an edge server by the lowest total latency can improve the system performance impressively.

Because most link-state routing protocols, such as OSPF and IS-IS, calculate routes using the Dijkstra algorithm, which poses scalability problems, implementors often introduce an artificial delay to reduce the number of route calculations. Although this delay directly affects IP packet forwarding, it can be acceptable when the network topology does not change often. However, when the topology of a network changes frequently, this delay can lead to a complete loss of IP reachability for the affected network prefixes during the unstable period. In this paper, we propose the Cached Shortest-path Tree (CST) approach, which speeds up intra-domain routing convergence without extra execution of the Dijkstra algorithm, even if the routing for a network is quite unstable. The basic idea of CST is to cache shortest-path trees (SPTs) of network topologies that appear frequently, and use these SPTs to instantly generate a routing table when the topology after a change matches one in the caches. CST depends on a characteristic that we found from an investigation of routing instability conducted on the WIDE Internet in Japan. That is, under unstable routing conditions, both frequently changing Link State Advertisements (LSAs) and their instances tend to be limited. At the end of this paper, we show CST's effectiveness by a trace-driven simulation.

Network virtualization environments (NVEs) are emerging to meet the increasing diversity of demands by Internet users where a virtual network (VN) can be constructed to accommodate each specific application service. In the future Internet, diverse service providers (SPs) will provide application services on their own VNs running across diverse infrastructure providers (InPs) that provide physical resources in an NVE. To realize both efficient resource utilization and good QoS of each individual service in such environments, SPs should perform adaptive control on network and computational resources in dynamic and competitive resource sharing, instead of explicit and sufficient reservation of physical resources for their VNs. On the other hand, two novel concepts, software-defined networking (SDN) and network function virtualization (NFV), have emerged to facilitate the efficient use of network and computational resources, flexible provisioning, network programmability, unified management, etc., which enable us to implement adaptive resource control. In this paper, therefore, we propose an architectural design of network orchestration for enabling SPs to maintain QoS of their applications aggressively by means of resource control on their VNs efficiently, by introducing virtual network provider (VNP) between InPs and SPs as 3-tier model, and by integrating SDN and NFV functionalities into NVE framework. We define new north-bound interfaces (NBIs) for resource requests, resource upgrades, resource programming, and alert notifications while using the standard OpenFlow interfaces for resource control on users' traffic flows. The feasibility of the proposed architecture is demonstrated through network experiments using a prototype implementation and a sample application service on nation-wide testbed networks, the JGN-X and RISE.