With the rapid expansion of IoT, there is a growing demand for efficient data processing and network load optimization. Service Function Chaining (SFC) has emerged as a key technology for distributed processing, particularly in edge computing environments. While SFC is traditionally implemented over IP networks, recent research has explored Named Data Networking (NDN) as a more flexible alternative, leveraging its content caching and name-based forwarding. However, NDN’s inherent request aggregation and multicast mechanisms introduce unique challenges in applying conventional distributed tracing techniques, which are crucial for SFC applications to understand potential root causes of problems.This paper proposes a distributed tracing method for NDN-based SFC (NDN SFC) that enables packet flow visualization and network latency analysis. Our method introduces logging agents on NDN routers to capture request flows and inter-node delays, which are then formatted using OpenTelemetry for seamless integration with visualization tools such as Grafana®and Jaeger.Our tracing method helps to optimize service chains, to enhance network performance evaluation, and to streamline debugging, making NDN SFC deployment more practical. By offering a more efficient alternative to traditional IP-based SFC, our method supports the practical adoption of NDN SFC in IoT and edge computing environments.

Interplanetary File System (IPFS) is a peer-to-peer distributed file system. It enables users to publish and retrieve contents with only an ID of the content. But IPFS suffers from high delay in publishing and retrieving contents. The reason is that IPFS uses Kademlia to calculate the location of contents. This means many message exchanges among IPFS peers. In this paper, we propose to use Named Data Networking to replace IPFS's Kademlia search as a way to improve the overall performance. Our current test results in a private network suggests great improvement when IPFS publish or retrieve contents.

The post-5th generation of mobile communications, Beyond 5G (B5G), receives attention and is being developed in countries. In Japan, B5G is expected to be the backbone of a future society that achieves economic development and the resolution of social issues. To achieve that, we need a mechanism for B5G to make all devices work together “autonomously” without human intervention. To achieve this autonomy, it is necessary to have an approach to network management and control that can perform without the complexity of networks due to the increased number of diverse services and technology to coordinate devices on the networks. Thus, we propose an Information-Centric Service Mesh (IC-SM) that offers dynamic name-based routing to cloud-native service mesh. We clarify the scalability issue of IC-SM to compare the performance of four network function disaggregation patterns.

Producer/content mobility is one of the issues in Information Centric Networking research. In this paper, we propose a simple mobility support solution exploiting caching capability and NLSR routing protocol in Named Data Networking. We validate the effectiveness of the proposed method by analyzing packets in various network configurations and measuring forwarding failure.

In order to simplify deployment and management of IoT services, Network Function Virtualization (NFV) and Service Function Chaining (SFC) are promising solutions, and much researchers have conducted these topics. To enhance the reliability of former research efforts, in this paper, we propose an orchestration framework for IoT-centric SFC by using Docker and Kubernetes. The framework enables an automatic IoT service deployment by satisfying service requirements and computing and network resource constraints. In such deployment, we apply a Virtual Network Function (VNF)/Service Function (SF) placement problem to achieve efficient utilization of the resources. We set an objective function as minimizing both numbers of SF instances and communications and build a mathematical model based on Integer Linear Programming (ILP). To validate it, we implement a model for the framework and evaluate the performances by carrying out a numerical evaluation and a real experiment. From the evaluation results, we confirm that the proposed approach can reduce the number of SF placements and the number of communications among SF instances.

Distributed Hash Table (DHT) has been widely applied to peer-to-peer (P2P) applications for efficient content lookup mechanisms. IPFS, one of the distributed systems for sharing files, websites, and data on a worldwide scale, adopts Kademlia as one of the DHTs, that is included in libp2p on the network layer of IFPS. Though DHT-based content lookup can scale in the number of peers, how to control lookup performance, e.g., lookup latency and lookup hop count, is one of the issues for a very large-scale network. Thus, it is necessary to guarantee both the lookup latency and the hop count even if the network scale becomes larger. In this paper, we propose a Kademlia alternative, called KadRTT, that reduces both the lookup latency and hop count. KadRTT has two functionalities, i.e., (i) RTT-based lookup target selection not to increase the maximum hop count, and (ii) uniform ID arrangement for each k-bucket to shorten the initial ID distance from content ID. Experimental results by the simulation show that KadRTT outperforms other Kademlia-based DHTs in terms of lookup latency and hop count.

Named Data Networking (NDN) is a new networking mechanism to amend problems in the current Internet. There are many features to improve the efficiency of network in NDN, and one of them is that routers can cache data conveyed by packets. This results in network node to client communication unlike the client to client principle in TCP/IP architecture. Therefore, end-to-end flow control cannot be applied to NDN unlike the Internet. Inspired from thermal diffusion, researchers proposed hop-by-hop flow control to solve this problem. However, the congestion control in hop-by-hop method is still under research. In this paper, a diffusion-based flow control method for NDN is proposed. We conducted simulations to verify its performance.

Virtualized service and network functions are deployed on virtual machines (VMs) to realize essential processing to realize service function chaining (SFC). Issues on SFC is SF allocation to a VM and to minimize the response time and number of function instances. In this paper, we propose an SF clustering-based scheduling algorithm, called "SF-clustering for utilizing virtual CPUs" (SFCUV), to solve the SF allocation and SF selection problems simultaneously. Experimental results show that SF-CUV can utilize vCPUs to minimize the response time.

As mobile multimedia services have significantly evolved and diversified with the spread of smartphones and Internet of Things (IoT) devices, low-delay multimedia cloud computing is the need of the hour. To address this demand, in this study, we introduce an edge cloud system that equips a multimedia service function chaining capability. A prototype implementation of the proposed edge cloud system has three main features: 1) edge computing deployment by using OpenStack, 2) multimedia service slicing and chaining, and 3) efficient resource management in edge networks. Based on these features, the proposed system achieves lower multimedia processing delay compared to a conventional cloud computing platform. We deploy the proposed system in our laboratory and validate the system performance by using typical multimedia application, such as human detection in video surveillance.

With the development of wireless communication technologies, the mobile terminal can be installed with more than one wireless interfaces to support its flexible roaming and vertical handover between heterogeneous access networks. Traditionally, the ongoing session has to be re-established when the multi-interface terminal hands over vertically while maintaining the Delay Tolerant Networking (DTN) communication. In this paper, a novel solution is proposed to efficiently support the on-demand DTN communication under the heterogeneous access networks based on Named Data Networking (NDN) architecture.

Parallelization paradigms for effective execution in a Directed Acyclic Graph (DAG) application have been widely studied in the area of task scheduling. Schedule length can be varied depending on task assignment policies, scheduling policies, and heterogeneity in terms of each processor and each communication bandwidth in a heterogeneous system. One disadvantage of existing task scheduling algorithms is that the schedule length cannot be reduced for a data intensive application. In this paper, we propose a clustering-based task scheduling algorithm called Clustering for Minimizing the Worst Schedule Length (CMWSL) to minimize the schedule length in a large number of heterogeneous processors. First, the proposed method derives the lower bound of the total execution time for each processor by taking both the system and application characteristics into account. As a result, the number of processors used for actual execution is regulated to minimize the Worst Schedule Length (WSL). Then, the actual task assignment and task clustering are performed to minimize the schedule length until the total execution time in a task cluster exceeds the lower bound. Experimental results indicate that CMWSL outperforms both existing list-based and clustering-based task scheduling algorithms in terms of the schedule length and efficiency, especially in data-intensive applications.

Data transfer of large files over the Internet is often performed using Peer-to-Peer (P2P) technology. BitTorrent is the most popular P2P content distribution application. In general, BitTorrent users have much higher download bandwidth than upload bandwidth. It leads to bottleneck problem under the lack of the upload bandwidth, and it drastically degrades the performance of the overall system. In this paper, we propose a method to utilize idle upload bandwidth of helper in order to improve the file sharing efficiency on the BitTorrent. We also evaluate the efficiency of the proposed method by using simulation.

The recent development of network technologies that offer centralized control of explicit routes opens the door to the online optimization of explicit routing. For this kind of Traffic Engineering optimization, raising the calculation speeds by using multi-core processors with effective parallel algorithms is a key goal. This paper proposes an effective parallel algorithm for General purpose Programming on Graphic Processing Unit (GPGPU); its massively parallel style promises strong acceleration of calculation speed. The proposed algorithm parallelizes not only the search method of the Genetic Algorithm, but also its fitness functions, which calculate the network congestion ratio, so as to fully utilize the power of modern GPGPUs. Concurrently, each execution is designed for thread-block execution on the GPU with consideration of thread occupancy, local resources, and SIMT execution to maximize GPU performance. Evaluations show that the proposed algorithm offers, on average, a nine fold speedup compared to the conventional CPU approach.

Network coding, with the redundant information it generates, has been shown to achieve optimal multicast throughput. Such redundancy plays a key role in maximizing throughput over multiple content delivery paths between network nodes. In this paper, we study the use of network coding to speed up content distribution in peer-to-peer networks where only a constraint number of selected peers can encode, i.e. become network coders. Our goal is to optimize the redundancy network coding generates, i.e. we want to answer the question how much a given network coder should encode. This serves as a step towards understanding how network coding improves content distribution in order to optimize its deployment. Given the network topology, we analytically figure the optimal redundancy ratio at each network coder to achieve shortest distribution time. Simulation results confirm the effectiveness of the proposed coding redundancy in shortening content distribution time while noticeably reducing the amount of encoding.

Network coding has been applied successfully in peer-to-peer (P2P) systems to shorten the distribution time. Pieces of data, i.e. blocks, are combined, i.e. encoded, by the sending peers before forwarding to other peers. Even though requiring all peers to encode might achieve shortest distribution time, it is not necessarily optimal in terms of computational resource consumption. Short finish time, in many cases, can be achieved with just a subset of carefully chosen peers. P2P systems, in addition, tend to be heterogeneous in which some peers, such as hand-held devices, would not have the required capacity to encode. We therefore envision a P2P system where some peers encode to improve distribution time and other peers, due to limited computational capacity or due to some system-wide optimization, do not encode. Such a system gives rise to a block-selection problem which has never happened in both pure non-coding and full network coding-enabled P2P systems. We identify the problem and fix the current block-selection algorithm to address it. Simulation evaluation confirms the effectiveness of our proposed algorithm without which the system performance degrades considerably.

Network coding has been applied successfully in peer-to-peer systems to shorten the distribution time, particularly in extreme conditions where peers in the network are clustered and separated by physical links with limited bandwidth. In this paper, we focus more closely on the use of source coding, i.e. encoding is done only at the source, as an alternative to network coding to facilitate content distribution under such limited bandwidth configuration. We observe analytically and experimentally that, in this specific case, with appropriately chosen expansion factors, source coding can have comparable performance to network coding in terms of distribution time, yet consuming much less computational resources than the latter approach does.

Future home appliances will have many useful built-in functions. A communication network that allows a user to access these built-in functions and to control the appliances is highly desirable. An ad hoc network can be easily deployed to connect these home appliances. For such a home network, ease of use must be given higher consideration. This paper discusses description based ad-hoc network routing where the nodes are given descriptions or keywords such as living room TV, kitchen oven etc. as identifiers. We propose three description based routing mechanisms: single routing cache, directional routing cache, and proportional-directional routing cache. Through simulation, we show that in all three methods the message delivery is 100% success in our configuration, but the amount of misdirected messages experienced by each method is different. The proportional-directional routing cache shows the least message misdirection with most preferable resource usage.

Divisible Load Theory (DLT) is an established mathematical framework to study Divisible Load Scheduling (DLS). However, traditional DLT does not comprehensively deal with the scheduling of results back to source (i.e., result collection) on heterogeneous systems. In this paper, the DLSRCHETS (DLS with Result Collection on HETerogeneous Systems) problem is addressed. The few papers to date that have dealt with DLSRCHETS, proposed simplistic LIFO (Last In, First Out) and FIFO (First In, First Out) type of schedules as solutions to DLSRCHETS. In this paper, a new heuristic algorithm, ITERLP, is proposed as a solution to the DLSRCHETS problem. With the help of simulations, it is proved that the performance of ITERLP is significantly better than existing algorithms.

Recently packet scheduling algorithms such as Packetized GPS (PGPS), worst-case fair weighted fair queueing (WF2Q) and Self-Clocked Fair Queueing (SCFQ) have been proposed in order to guarantee deterministic or statistical delay bounds. These algorithms are based on generalized processor sharing (GPS) which is an ideal scheduling algorithm based on fluid flow model in which the traffic is infinitely divisible. GPS provides a minimum guaranteed service rate for each session and tight delay bounds for leaky bucket constrained sessions. However, the delay bounds are unnecessarily large because each session is served according to its associated constant weight until the session buffer is empty. In this paper, we present a scheduling policy called output rate-controlled generalized processor sharing (ORC-GPS). ORC-GPS is a rate-based scheduling like GPS and controls the service rate to lower the delay bounds for leaky bucket constrained sessions. In numerical experiments, we compare ORC-GPS with GPS in terms of delay bounds.

QoS control for multicast over the Internet is necessary to provide high quality multicast video streaming. With existing DiffServ multicast schemes, multicast traffic in a DiffServ domain increases as the multicast-group membership grows, and consequently packets guaranteed for delivery may be discarded. Since it is hard to guarantee QoS for all flows over the entire network, we propose DERACS a delivery range control scheme which guarantees QoS in a limited delivery range formed by actively discarding packets. In this paper, we show the delivery range of DERACS through simulation and analysis.

In this paper we present a new token based protocol for group mutual exclusion in distributed systems. The protocol uses one single token to allow multiple processes to enter the critical section for a common session. One of the significant characteristics of the protocol is - concurrency, throughput and waiting time can be regulated adjusting the time period for which a session is declared. The minimum and the maximum number of messages to enter the CS is 0 and ( n + 2) respectively where n is the total number of processes in the system. Moreover, simulation results show that the protocol, on average case, considerably reduces the number of messages per entry to the CS and also requires much lower waiting times. The maximum concurrency the protocol supports is n. The protocol also ensures no starvation in the system. Furthermore, this algorithm works out for the Extended Group Mutual Exclusion problem as well.

Speech services are widely deployed on new communication infrastructures. However, compared with traditional infrastructures, the ever varying conditions are native of these new infrastructures. Modeling the time-varying speech quality becomes an urgent issue. This paper proposes a computable model for time-varying speech quality evaluation, called M-Model. Considering the time-varying issue, EWMA is used in the model. M-Model is validated by a subjective experiment. The model indicates that time-varying quality with extremely high frequency does not affect perceived quality at all. In addition, we observed that the recency effect influences not only the perceived overall quality but also the perceived instantaneous quality.

P2P content distribution networks are collecting interest to efficiently deliver rich contents such as audio and video. Stream interruption caused by relay peers dropping out of the P2P network is a problem in P2P live streaming systems. In this paper, we propose a P2P live streaming system with low stream interruption. In the proposed system, peers are connected to the peers with low drop-out probability and a wide and short P2P network is constructed. Also, multiple paths to the source is considered. We show the improvement in the interruption time by our algorithm through simulations.

The demand to access multimedia data such as live video is increasing due to the spread of broadband access network. However, the Internet only provides the so called best-effort service. The network condition of the Internet shows fluctuation. Delivering video without any control causes degradation of the final video quality. To avoid such degradation, we must control video traffic to adapt to the fluctuating available bandwidth. In this paper, we propose a technique to find the available bandwidth for end-to-end stream connections over the Internet. We claim that the correlation coefficient of the network delay of an end-to-end stream is closely related to the bottleneck-link load for the end-to-end stream connection. We show and prove the relationship through analysis and simulations.

The demand to access multimedia data such as live video is increasing due to the spread of broadband access network. However, the Internet only provides so called best-effort service. The network condition of the Internet shows fluctuation. Delivering video without any control causes degradation of the final video quality. In this paper we propose a stream-rate control algorithm RC/sup 3/ that uses correlation of network delay to evaluate available bandwidth. We show performance of RC/sup 3/ derived from simulations.

From the trend of open network computing arose the demand for the standardization of the distributed processing environment (DPE). The telecommunications industry is also aware of the benefit of DPE in order to reduce the development cost and to provide advanced services quickly. On the user side, customer premises equipment now have significant processing power, and the trend of computer-telephony integration (CTI) is progressing both at home and in offices. By integrating the telecommunications systems with home and office computers, the customers can enjoy flexible telecommunication services. DPE can provide a basic framework necessary for the integration. This paper proposes an architecture for extending telecom-DPE to home and offices, called "interpreter bridge architecture", which enables carriers to provide flexible telecommunication services.

The problem of assigning execution intervals for periodic transactions in real-time databases is discussed. The object value evolution rate and the importance of the object are used as two factors for deciding transaction periods. Two different objective functions are defined to reflect different system design goals. Algorithms for optimizing each objective function are presented. The principle behind these algorithms is to allow the transactions which have higher weights to be executed more often. It is assumed that systems use the rate monotonic algorithm for scheduling transactions. Many other scheduling algorithms, like the earliest deadline first algorithm can also be used. Some examples using the proposed algorithms are given.>