Heterogeneous drone swarms are large hybrid drone clusters in which multiple drones with different wireless protocols are interconnected by some translator drones called GWs. Nowadays, because inexpensive drones, such as toy drones, have become widely used in society, the technology for constructing huge drone swarms is attracting more and more attention. In this paper, we propose an autonomous GW mobility control algorithm for establishing stabilized and low-delay communication among heterogeneous clusters, assuming that only GWs are controllable and relocatable to ensure the flexible operationality of drone swarms. Our proposed algorithm is composed of two independent sub algorithms - the Link Stabilizer and the Path Optimizer. The Stabilizer maintains the neighbor links and consists of two schemes: the neighbor clustering based on relative velocities and the GW velocity calculation using a kinetic model. The Optimizer creates a shortcut to reduce the end-to-end delay for newly established communication by relocating the GW dynamically. We also propose a conceptual protocol design to implement this algorithm into real-world drone swarms in a distributed manner. Computer simulation reveals that the Stabilizer improved the connection stability for all three mobility models even under the high node mobility, and the Optimizer reduced the communication delay by the optimal shortcut formation under any conditions of the experiments and its performance is comparable to the performance upper limit obtained by the brute-force searching.

We have developed a new method to improve cooperation in concurrent systems for distributed control by using multi-agent (MA) functions. Since field terminals (FTs) work concurrently, cooperation among them is essential to the effectiveness and efficiency of the overall system. When FTs are modeled as agents, it is easy to explicitly deal with the interactions among them because those interactions can be modeled naturally as communication among agents with cooperation and negotiation. In conventional central control systems, the host computer supervises and controls all FTs in accordance with a pre-installed control algorithm. Our method instead uses intelligent field terminals (IFTs) that can evaluate the diverse information from devices of other IFTs autonomously. In the work reported here, we have evaluated the effectiveness and efficiency of our cooperative control method experimentally and have developed a system using this method to control various kinds of water delivery systems. The IFT providing MA functions that can evaluate the control parameters (CPs) and conditions of the other IFTs. If turn-around time is to be shortened, the conflicts that occur when the data processed by different IFTs is inconsistent or irregular must be resolved autonomously. Each IFT therefore cooperates with diverse functional agents (FA)s of other IFTs by using priority levels, conditions, and evaluation points in order to maintain the continuity of water delivery.

We have proposed a novel call admission control (CAC) for maximizing total user satisfaction in a heterogeneous traffic network and showed the effectiveness of our CAC by using an optimal threshold from numerical analysis [1]. In our previous CAC, when a new broadband flow arrives and the total accommodated bandwidth is more than or equal to the threshold, the arriving new broadband flow is rejected. In actual networks, however, users may agree to wait for a certain period until the broadband flow, such as video, begins to play. In this paper, when total accommodated bandwidth is more than or equal to the threshold, arriving broadband flows wait instead of being rejected. As a result, we can greatly improve total user satisfaction.

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.

In this paper, we propose an autonomously distributed QoS control method for MPEG video streaming in a wide area network. The capacity of the links and the characteristics of video streams change dynamically. However, managing the condition of all the links and streams in the network is difficult. In the proposed method, the routers in the network monitor the conditions of the links and streams locally and control the transmission rate of the stream server. Picture-quality oriented fairness is achieved by reducing the transmission rate of the streams with the higher PSNR in the bottleneck link. The computer simulation results show that the proposed method can be applied to a wide area network.

Solving image recovery problems requires the use of some efficient regularizations based on a priori information with respect to the unknown original image. Naturally, we can assume that an image is modeled as the sum of smooth, edge, and texture components. To obtain a high quality recovered image, appropriate regularizations for each individual component are required. In this paper, we propose a novel image recovery technique which performs decomposition and recovery simultaneously. We formulate image recovery as a nonsmooth convex optimization problem and design an iterative scheme based on the alternating direction method of multipliers (ADMM) for approximating its global minimizer efficiently. Experimental results reveal that the proposed image recovery technique outperforms a state-of-the-art method.

Multimedia applications such as video and audio have recently come into much wider use. Because this heterogeneous traffic consumes most of the network's resources, call admission control (CAC) is required to maintain high-quality services. User satisfaction depends on CAC's success in accommodating application flows. Conventional CACs do not take into consideration user satisfaction because their main purpose is to improve the utilization of resources. Moreover, if we assume a service where an ISP provides a "flat-based charging," each user may receive same user satisfaction as a result of users being accommodated in a network, even if each has a different bandwidth. Therefore, we propose a novel CAC to maximize total user satisfaction based on a new philosophy where heterog eneous traffic is treated equally in networks. Theoretical analysis is used to derive optimal thresholds for various traffic configurations with a full search system. We also carried out theoretical numerical analysis to demonstrate the effectiveness of our new CAC. Moreover, we propose a sub-optimal threshold configuration obtained by using an approximation formula to develop practical CAC from these observations. We tested and confirmed that performance could be improved by using sub-optimal parameters.

Live streaming is delay sensitive and can tolerate some amount of loss. The QoS Multicast for Live Streaming (QMLS) Protocol, focuses on the characteristics of live streaming. It has been shown to improve the performance of live streaming multicast by reducing the end-to-end packet loss probability. However, the placement of active routers performing the QMLS function has not been discussed. This paper proposes a dynamic method to activate and deactivate routers in order to minimize the number of active routers for each QMLS-packet flow and discusses its parameters. The results of an evaluation show that the proposed method can reduce the number of active routers for each flow and adjust the active routers according to changes in the multicast tree.

We have proposed a novel call admission control (CAC) method for maximizing total user satisfaction in a heterogeneous traffic network and showed their effectiveness by using the optimal threshold from numerical analysis [1],[2]. With these CAC methods, it is assumed that only selfish users exist in a network. However, we need to consider the possibility that some cooperative users exist who would agree to reduce their requested bandwidth to improve another user's Quality of Service (QoS). Under this assumption, conventional CAC may not be optimal. If there are cooperative users in the network, we need control methods that encourage such user cooperation. However, such “encourage” control methods have not yet been proposed. Therefore, in this paper, we propose novel CAC methods for cooperative users by using queueing theory. Numerical analyses show their effectiveness. We also analyze the characteristics of the optimal control parameter of the threshold.

We propose an optimal access-point (AP) selection algorithm for maximizing the aggregated throughput of each AP (system throughput) while preserving newly arrived-user throughput in multi rate WLAN system. In our algorithm, newly arrived users cooperate with a wireless local area network (WLAN) system they are trying to use, i.e., they are willing to move toward an appropriate AP before the newly arrived user connects to AP. To select the AP by using our AP selection algorithm, the newly arriving users request two novel parameter values, “the minimum acceptable throughput” with which newly arrived users can be satisfied and “the minimum movable distance” in which a user can move to an appropriate AP. While preserving these conditions, we maximize system throughput. When users cannot obtain a throughput greater than “the minimum acceptable throughput” with our proposed AP selection algorithm, they are rejected. Because, if users use streaming applications, which have strict bandwidth demands, with a very low bit-rate connection, they will not be satisfied. Thus, the newly arrived users having low bit-rate connection may be allowed to be rejected before the newly arrived user connects. In this paper, we show the optimal AP by using theoretical proof. We discuss the effectiveness of our proposed AP selection algorithm by using numerical analysis. We also clarify and analyze the characteristics of system throughput. Moreover, we show that a newly arrived user can select the movable distance and acceptable throughput by using examples from graphs depicting every position of newly arrived users. By using the graphs, we also show the relationship between the two parameters (the movable distance and the acceptable throughput) and the optimal AP, and the relationship between the two parameters and optimal system throughput when the movable distance and acceptable throughput are variable.

Software-Defined Networking (SDN) can be applied for managing application flows dynamically by a logically centralized SDN controller and SDN switches. Because one SDN switch can support just a few thousand forwarding rule installations per second, it is a barrier to dynamic and scalable application flow management. For this reason, it is essential to reduce the number of application flows if they are to be successfully managed. Nowadays, since much attention has been paid to developing a network service that reduces application delay, the allowable delay of application flows has become an important factor. However, there has been no work on minimizing the number of flows while satisfying end-to-end delay of flows. In this paper, we propose a method that can aggregate flows and minimize the number flows in a network while ensuring all flows satisfy their allowable delay in accordance with QoS or SLA. Since the problem is classified as NP-hard, we propose a heuristic algorithm. We compared the aggregation effect of the proposed method, simple aggregation method and optimal solution by simulation. In addition, we clarify the characteristics of the proposed method by performing simulations with various parameter settings. The results show that the proposed method decreases the number of rules than comparative aggregation method and has very shorter computational time than optimal solution.

The 5G mobile network environment has been studied and developed, and the concept of a vEPC (Virtualized Evolved Packet Core) has been introduced as a framework for Network Functions Virtualization (NFV). Machine-to-Machine (M2M) communications in 5G networks require much faster response than are possible in 4G networks. However, if both the control plane (C-plane) and the data plane (D-plane) functions of the EPC are migrated into a single vEPC server, M2M devices and other user equipments (UEs) share the same resources. To accommodate delay-sensitive M2M sessions in vEPC networks, not only signaling performance on the C-plane but also packet processing performance on the D-plane must be optimized. In this paper, we propose a method for optimizing resource assignment of C-plane and D-plane Virtualized Network Functions (VNFs) in a vEPC server, called the vEPC-ORA method. We distinguish the communications of M2M devices and smartphones and model the vEPC server by using queueing theory. Numerical analysis of optimal resource assignment shows that our proposed method minimizes the blocking rates of M2M sessions and smartphone sessions. We also confirmed that the mean packet processing time is kept within the allowable delay for each communication type, as long as the vEPC server has enough VM resources. Moreover, we study a resource granularity effect on the optimal resource assignment. Numerical analysis under a fixed number of hardware resources of MME and S/P-GW is done for various resource granularities of the vEPC server. The evaluation results of numerical analyses showed that the vEPC-ORA method derives the optimal resource assignment in practical calculation times.

Many content distribution systems such as CDN and P2P file sharing have been developed. In these systems, file-type contents require downloads to be completed before they can be played and they have no value before the download finishes. Therefore, a user's satisfaction depends on the length of the service latency. That is, the length of time from when the user issued a request until the user received an entire file. Reducing the sum of that time is necessary for the whole delivery system to satisfy users and maintain dependability on system performance. We discuss a hop-by-hop file delivery system suitable for delivering file contents whereby the sum of service latency is reduced by using the request conditions. Moreover, we propose a file delivery scheduling algorithm for a one-link model given that the content request frequency is unknown. The algorithm is based on a local optimal strategy. We performed a characteristic analysis by computer simulation. The results showed that our algorithm performs at nearly the theoretical efficiency limit of the hop-by-hop system when the request frequency distribution of each content has a deviation.

This paper looks at the history of research in the Technical Committee on Information Networks from the time of its inception to the present and provides an overview of the latest research in this area based on the topics discussed in recent meetings of the committee. It also presents possible future developments in the field of information networks.

A drone swarm is a robotic architecture having multiple drones cooperate to accomplish a mission. Nowadays, heterogeneous drone swarms, in which a small number of gateway drones (GWs) act as protocol translators to enable the mixing of multiple swarms that use independent wireless protocols, have attracted much attention from many researchers. Our previous work proposed Path Optimizer — a method to minimize the number of end-to-end path-hops in a remote video monitoring system using heterogeneous drone swarms by autonomously relocating GWs to create a shortcut in the network for each communication request. However, Path Optimizer has limitations in improving communication quality when more video sessions than the number of GWs are requested simultaneously. Path Coordinator, which we propose in this paper, achieves a uniform reduction in end-to-end hops and maximizes the allowable hop satisfaction rate regardless of the number of sessions by introducing the cooperative and synchronous relocation of all GWs. Path Coordinator consists of two phases: first, physical optimization is performed by geographically relocating all GWs (relocation phase), and then logical optimization is achieved by modifying the relaying GWs of each video flow (rerouting phase). Computer simulations reveal that Path Coordinator adapts to various environments and performs as well as we expected. Furthermore, its performance is comparable to the upper limits possible with brute-force search.

In emergency situations, telecommunication networks become congested due to large numbers of call requests. Also, some infrastructure breaks down, so undamaged communication resources must be utilized more efficiently. Therefore, several lines in telephone exchanges are generally reserved for emergency calls whose users communicate crucial information. The number of lines reserved for emergency calls is determined by a threshold, on a trunk reservation control method. To accept both required emergency calls and more general calls, the traffic intensity of arriving emergency calls should be estimated in advance, and a threshold should be configured so that the number of reserved lines becomes lower than the estimation. Moreover, we propose that the holding time for general calls should be positively limited. By guaranteeing the holding time sufficient for communicating essential information, holding time limitation reduces long-period calls so more general calls are accepted. In this paper, we propose a new CAC method to utilize undamaged communication resources more efficiently during emergencies. Our proposed method accepts more general calls by collaboratively relaxing the threshold of trunk reservation and limiting holding time of general calls. This method is targeted at not only the telephone exchange but also various systems on networks, e.g. base stations of the wireless network or SIP servers. With our method, the threshold is configured in consideration of the ratio of traffic intensities estimated in advance. We modeled the telephone exchange as a queueing loss system and calculated call-blocking rates of both emergency and general calls by using computer simulation. The comparison with the conventional holding time limitation method showed that our proposed method accepts the required number of emergency calls by appropriately relaxing the threshold, while suppressing the increase in call-blocking of general calls.

Live streaming media are delay sensitive and have limited allowable delays. Current conventional multicast protocols do not have a loss retransmission mechanism. Even though several reliable multicast protocols with retransmission mechanisms have been proposed, the long delay and high packet loss rate make them inefficient for live streaming. This paper proposes a multicast protocol focusing on the allowable delay called the QoS Multicast for Live Streaming (QMLS) protocol. QMLS routers are placed along the multicast tree to detect and retransmit lost packets. We propose a method that enables data recovery to be done immediately after lost packets are detected by the QMLS router and a method that reduces the unnecessary packets sent to end receivers. This paper discusses the mathematical analysis of the proposed protocol and compares it with other multicast protocols. The results reveal that our protocol is more effective in live streaming. Finally, we do a simulation to evaluate its performance and study the effect of consecutive losses. The simulation reveals that consecutive losses can slightly increase losses with our protocol.

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.

Admission control is becoming an essential technique for IP networks to provide full-fledged multimedia streaming services. Although signaling-based schemes are utilized to achieve this, these are difficult to deploy and can hardly achieve strict admission control taking the properties of packet arrival into consideration. In this paper, we propose a novel admission control strategy called the Tentative Accommodating and Congestion Confirming Strategy (TACCS). The main idea is to accommodate incoming flows tentatively and confirm congestion after a certain period. Since tentative accommodating enables us to generate the same situation as where incoming flows have been accommodated, TACCS makes it possible to control admission considering the properties of packet arrival after they have been accommodated, without collecting resource information in advance. From the results of mathematical analysis, we confirmed that TACCS enabled a domain to control admission without a centralized management agent and we provided guidelines for configuring parameters of TACCS.

When an IP Multicast network is constructed on a switch-based network, many IP Multicast packet broadcasts are generated, and these broadcasts cause trouble for all of the other kinds of communication. To solve this problem, implementing IGMP Snooping on various switches has been proposed. However, some switches have insufficient IP Multicast packet-handling capability. This problem is also mentioned in RFC4541. In this paper, we propose the IGMP Snooping Activator (ISA) mechanism as a way to solve the IP Multicast packet-handling problem. The ISA transmits dummy IGMP Queries to maintain the IP Multicast network, and it joins the flooding IP Multicast group to activate IGMP Snooping in switches that are unable to handle IP Multicast packets. The experimental evaluation shows the effectiveness of our proposed method: the network load decreases because of the method's effective restraint of IP Multicast packet flooding.