Blockchain systems rely on peer-to-peer (P2P) overlay networks to propagate transactions and blocks. The node management of P2P networks affects the overall performance and reliability of the system. The traditional structure is based on random connectivity, which is known to be an inefficient operation. Therefore, we propose MSLT, a multiscale blockchain P2P network node management method to improve transaction performance. This approach involves configuring the network to operate at multiple scales, where blockchain nodes are grouped into different ranges at each scale. To minimize redundancy and manage traffic efficiently, neighboring nodes are selected from each range based on a predetermined set of rules. Additionally, a node updating method is implemented to improve the reliability of the network. Compared with existing transmission models in efficiency, utilization, and maximum transaction throughput, the MSLT node management model improves the data transmission performance.

Cell-free massive MIMO (CF-mMIMO), which cooperatively utilizes a large number of antennas deployed over a communication area, has been attracting great attention as an important technology for realizing 5G-advanced and 6G systems. Recently, to ensure system scalability and mitigate inter-user interference in CF-mMIMO, a user-centric (UC) approach was investigated. In this UC approach, user-centric antenna-sets are formed by selecting appropriate antennas for each user, and postcoding is applied to reduce the strong interference from users whose antenna-sets overlap. However, in very high user density environments, since the number of interfering users increases due to increased overlapping of antenna-sets, the achievable link capacity may degrade. In this paper, we propose a user-cluster-centric (UCC) approach, which groups neighborhood users into a user-cluster and associates the predetermined number of antennas to this user-cluster for spatial multiplexing. We derive the uplink postcoding weights and explain the effectiveness of the proposed UCC approach in terms of the computational complexity of the weight computation. We also compare the uplink user capacities achievable with UC and UCC approaches by computer simulation and clarify situations where the UCC approach is effective. Furthermore, we discuss the impact of the number of interfering users considered in the zero-forcing and minimum mean square error postcoding weight computation on the user capacity.

The total number of solar power-producing facilities whose Feed-in Tariff (FIT) Program-based ten-year contracts will expire by 2023 is expected to reach approximately 1.65 million in Japan. If the facilities that produce or consume renewable energy would increase to reach a large number, e.g., two million, blockchain would not be capable of processing all the transactions. In this work, we propose a blockchain-based electricity-tracking platform for renewable energy, called ‘ZGridBC,’ which consists of mutually cooperative two novel decentralized schemes to solve scalability, storage cost, and privacy issues at the same time. One is the electricity production resource management, which is an efficient data management scheme that manages electricity production resources (EPRs) on the blockchain by using UTXO tokens extended to two-dimension (period and electricity amount) to prevent double-spending. The other is the electricity-tracking proof, which is a massive data aggregation scheme that significantly reduces the amount of data managed on the blockchain by using zero-knowledge proof (ZKP). Thereafter, we illustrate the architecture of ZGridBC, consider its scalability, security, and privacy, and illustrate the implementation of ZGridBC. Finally, we evaluate the scalability of ZGridBC, which handles two million electricity facilities with far less cost per environmental value compared with the price of the environmental value proposed by METI (=0.3 yen/kWh).

5G service has been launched in various countries, and research for the beyond 5G is already underway actively around the world. In beyond 5G, it is expected to expand the various capabilities of communication technologies to cover further wide use cases from 5G. As a candidate elemental technology, cell free massive MIMO has been widely researched and shown its potential to enhance the capabilities from various aspects. However, for deploying this technology in reality, there are still many technical issues such as a cost of distributing antenna and installing fronthaul, and also the scalability aspects. This paper surveys research trends of cell free massive MIMO, especially focusing on the deployment challenges with an introduction to our specific related research activities including some numerical examples.

Real-time and scalable multicast services are of paramount importance to Industrial Internet of Things (IIoT) applications. To realize these services, the multicast algorithm should, on the one hand, ensure the maximum delay of a multicast session not exceeding its upper delay bound. On the other hand, the algorithm should minimize session costs. As an emerging networking paradigm, Software-defined Networking (SDN) can provide a global view of the network to multicast algorithms, thereby bringing new opportunities for realizing the desired multicast services in IIoT environments. Unfortunately, existing SDN-based multicast (SDM) algorithms cannot meet the real-time and scalable requirements simultaneously. Therefore, in this paper, we focus on SDM algorithm design for IIoT environments. To be specific, the paper first converts the multicast tree construction problem for SDM in IIoT environments into a delay-bounded least-cost shared tree problem and proves that it is an NP-complete problem. Then, the paper puts forward a shared tree (ST) algorithm called SDM4IIoT to compute suboptimal solutions to the problem. The algorithm consists of five steps: 1) construct a delay-optimal shared tree; 2) divide the tree into a set of subpaths and a subtree; 3) optimize the cost of each subpath by relaxing the delay constraint; 4) optimize the subtree cost in the same manner; 5) recombine them into a shared tree. Simulation results show that the algorithm can provide real-time support that other ST algorithms cannot. In addition, it can achieve good scalability. Its cost is only 20.56% higher than the cost-optimal ST algorithm. Furthermore, its computation time is also acceptable. The algorithm can help to realize real-time and scalable multicast services for IIoT applications.

This paper describes a novel 4K 120fps (frames per second) real-time HEVC (High Efficiency Video Coding) encoder for high-frame-rate video encoding and transmission. Motion portrayal problems such as motion blur and jerkiness may occur in video scenes containing fast-moving objects or quick camera panning. A high-frame-rate solves such problems and provides a more immersive viewing experience that can express even the fast-moving scenes without discomfort. It can also be used in remote operation for scenes with high motion, such as VAR (Video Assistant Referee) systems in sports. Real-time encoding of high-frame-rate videos with low latency and temporal scalability is required for providing such high-frame-rate video services. The proposed encoder achieves full 4K/120fps real-time encoding, which is twice the current 4K service frame rate of 60fps, by multichip configuration with two encoder LSI. Exchange of reference picture data near a spatially divided slice boundary provides cross-chip motion estimation, and maintains the coding efficiency. The encoder supports temporal-scalable coding mode, in which it output stream with temporal scalability transmitted over one or two transmission paths. The encoder also supports the other mode, low-delay coding mode, in which it achieves 21.8msec low-latency processing through motion vector restriction. Evaluation of the proposed encoder's multichip configuration shows that the BD-bitrate (the average rate of bitrate increase), compared to simple slice division without inter-chip transfer, is -2.86% at minimum and -2.41% on average in temporal-scalable coding mode. The proposed encoder system will open the door to the next generation of high-frame-rate UHDTV (ultra-high-definition television) services.

Scalable networking for scientific research data transfer is a vital factor in the progress of data-intensive research, such as collaborative research on observation of black hole. In this paper, investigations of the nature of practical research traffic allow us to introduce optical flow switching (OFS) and contents delivery network (CDN) technologies into a wide area network (WAN) to realize highly scalable networking. To measure the scalability of networks, energy consumption in the WAN is evaluated by considering the practical networking equipment as well as reasonable assumptions on scientific research data transfer networks. In this study, we explore the energy consumption performance of diverse Japan and US topologies and reveal that the energy consumption of a routing and wavelength assignment algorithm in an OFS scheduler becomes the major hurdle when the number of nodes is high, for example, as high as that of the United States of America layer 1 topology. To provide computational scalability of a network dimensioning algorithm for the CDN based WAN, a simple heuristic algorithm for a surrogate location problem is proposed and compared with an optimal algorithm. This paper provides intuitions and design rules for highly scalable research data transfer networks, and thus, it can accelerate technology advancements against the encountering big-science problems.

Designing an optimum quantizer can be treated as the optimization problem of finding the quantization indices that minimize the quantization error. One solution to the optimization problem, DP quantization, is based on dynamic programming. Some applications, such as bit-depth scalable codec and tone mapping, require the construction of multiple quantizers with different quantization levels, for example, from 12bit/channel to 10bit/channel and 8bit/channel. Unfortunately, the above mentioned DP quantization optimizes the quantizer for just one quantization level. That is, it is unable to simultaneously optimize multiple quantizers. Therefore, when DP quantization is used to design multiple quantizers, there are many redundant computations in the optimization process. This paper proposes an extended DP quantization with a complexity reduction algorithm for the optimal design of multiple quantizers. Experiments show that the proposed algorithm reduces complexity by 20.8%, on average, compared to conventional DP quantization.

In this paper, we describe a novel low-delay 4K 120-fps real-time HEVC decoder with a parallel processing architecture that conforms to the HEVC main 4:2:2 10 profile. It supports the hierarchical temporal scalable streams required for Ultra High Definition high-frame-rate broadcasting and also supports low-delay and high-bitrate decoding for video transmission uses. To achieve this support, the decoding processes are parallelized and pipelined at the frame level, slice level, and coding tree unit row level. The proposed decoder was implemented on three FPGAs operated at 133 and 150 MHz, and it achieved 300-Mbps stream decoding and 37-msec end-to-end delay with our concurrently developed 4K 120-fps encoder.

Group signatures are signatures providing signer anonymity where signers can produce signatures on behalf of the group that they belong to. Although such anonymity is quite attractive considering privacy issues, it is not trivial to check whether a signer has been revoked or not. Thus, how to revoke the rights of signers is one of the major topics in the research on group signatures. In particular, scalability, where the signing and verification costs and the signature size are constant in terms of the number of signers N, and other costs regarding signers are at most logarithmic in N, is quite important. In this paper, we propose a revocable group signature scheme which is currently more efficient compared to previous all scalable schemes. Moreover, our revocable group signature scheme is secure under simple assumptions (in the random oracle model), whereas all scalable schemes are secure under q-type assumptions. We implemented our scheme by employing a Barreto-Lynn-Scott curve of embedding degree 12 over a 455-bit prime field (BLS-12-455), and a Barreto-Naehrig curve of embedding degree 12 over a 382-bit prime field (BN-12-382), respectively, by using the RELIC library. We showed that the online running times of our signing algorithm were approximately 14msec (BLS-12-455) and 11msec (BN-12-382), and those of our verification algorithm were approximately 20msec (BLS-12-455) and 16msec (BN-12-382), respectively. Finally, we showed that our scheme (with a slight extension) is applied to an identity management system proposed by Isshiki et al.

At EUROCRYPT 2012, Libert, Peters and Yung (LPY) proposed the first scalable revocable group signature (R-GS) scheme in the standard model which achieves constant signing/verification costs and other costs regarding signers are at most logarithmic in N, where N is the maximum number of group members. However, although the LPY R-GS scheme is asymptotically quite efficient, this scheme is not sufficiently efficient in practice. For example, the signature size of the LPY scheme is roughly 10 times larger than that of an RSA signature (for 160-bit security). In this paper, we propose a compact R-GS scheme secure in the random oracle model that is efficient not only in the asymptotic sense but also in practical parameter settings. We achieve the same efficiency as the LPY scheme in an asymptotic sense, and the signature size is nearly equal to that of an RSA signature (for 160-bit security). It is particularly worth noting that our R-GS scheme has the smallest signature size compared to those of previous R-GS schemes which enable constant signing/verification costs. Our technique, which we call parallel Boneh-Boyen-Shacham group signature technique, helps to construct an R-GS scheme without following the technique used in LPY, i.e., we directly apply the Naor-Naor-Lotspiech framework without using any identity-based encryption.

Since the hardware resource of a single FPGA is limited, one idea to scale the performance of FPGA-based HPC applications is to expand the design space with multiple FPGAs. This paper presents a scalable architecture of a deeply pipelined stream computing platform, where available parallelism and inter-FPGA link characteristics are investigated to achieve a scaled performance. For a practical exploration of this vast design space, a performance model is presented and verified with the evaluation of a tsunami simulation application implemented on Intel Arria 10 FPGAs. Finally, scalability analysis is performed, where speedup is achieved when increasing the computing pipeline over multiple FPGAs while maintaining the problem size of computation. Performance is scaled with multiple FPGAs; however, performance degradation occurs with insufficient available bandwidth and large pipeline overhead brought by inadequate data stream size. Tsunami simulation results show that the highest scaled performance for 8 cascaded Arria 10 FPGAs is achieved with a single pipeline of 5 stream processing elements (SPEs), which obtained a scaled performance of 2.5 TFlops and a parallel efficiency of 98%, indicating the strong scalability of the multi-FPGA stream computing platform.

Distributed control plane architecture has been employed in software-defined data center networks to improve the scalability of control plane. However, since the flow space is partitioned by assigning switches to different controllers, the network topology is also partitioned and the rule setup process has to invoke multiple controllers. Besides, the control load balancing based on switch migration is heavyweight. In this paper, we propose a lightweight load partition method which decouples the flow space from the network topology. The flow space is partitioned with hosts rather than switches as carriers, which supports fine-grained and lightweight load balancing. Moreover, the switches are no longer needed to be assigned to different controllers and we keep all of them controlled by each controller, thus each flow request can be processed by exactly one controller in a centralized style. Evaluations show that our scheme reduces rule setup costs and achieves lightweight load balancing.

In this paper, we propose the first identity-based dynamic multi-cast key distribution (ID-DMKD) protocol which is secure against maximum exposure of secret information (e.g., secret keys and session-specific randomness). In DMKD protocols, users share a common session key without revealing any information of the session key to the semi-honest server, and can join/leave to/from the group at any time even after establishing the session key. Most of the known DMKD protocols are insecure if some secret information is exposed. Recently, an exposure resilient DMKD protocol was introduced, however, each user must manage his/her certificate by using the public-key infrastructure. We solve this problem by constructing the DMKD protocol authenticated by user's ID (i.e., without certificate). We introduce a formal security definition for ID-DMKD by extending the previous definition for DMKD. We must carefully consider exposure of the server's static secret key in the ID-DMKD setting because exposure of the server's static secret key causes exposure of all users' static secret keys. We prove that our protocol is secure in our security model in the standard model. Another advantage of our protocol is scalability: communication and computation costs of each user are independent from the number of users. Furthermore, we show how to extend our protocol to achieve non-interactive join by using certificateless encryption. Such an extension is useful in applications that the group members frequently change like group chat services.

Information-Centric Networking (ICN) treats contents as first class citizens and adopts name-based routing for content distribution and retrieval. Content names rather than IP addresses are directly used for routing. However, due to the location-independent naming and the huge namespace, name-based routing faces scalability and efficiency issues including large routing tables and high path stretches. This paper proposes a universal Scalable Name-based Geometric Routing scheme (SNGR), which is a careful synthesis of geometric routing and name resolution. To provide scalable and efficient underlying routing, a universal geometric routing framework (GRF) is proposed. Any geometric routing scheme can be used directly for name resolution based on GRF. To implement an overlay name resolution system, SNGR utilizes a bi-level grouping design. With this design, a resolution node that is close to the consumer can always be found. Our theoretical analyses guarantee the performance of SNGR, and experiments show that SNGR outperforms similar routing schemes in terms of node state, path stretch, and reliability.

Low pin-count testing is an effective method to reduce test cost. Based on this method multi-site testing, i.e., where multiple devices are tested concurrently, can be supported under the limitation on the number of channels provided by ATE. In this work we propose a scalable test module (called STM) design that can support multi-site testing more efficiently when compared with previous work. In the previous work, the total number of devices that can be tested concurrently is usually fixed when the design for testability hardware is designed. For our STM, each STM can deal with a number of circuits to be tested at the same time. Moreover, STM is scalable, i.e., multiple STMs can work collaboratively while the ATE bandwidth still remains the same to further increase the degree of test parallelism. Our STM will be integrated with ATE and serve as an interface between ATE and circuits under test (CUT). Only four pins are required by STM to communicate with ATE, and IEEE 1149.1 Std. ports are employed to transfer test data to/from CUTs. STM has been verified via silicon proof, which contains only about 2,768 logic gates. Experiments results for a number of ISCAS and IWLS'05 benchmark circuits also demonstrate that by making good use of the scalable feature of STM, test efficiency can be enhanced significantly.

As the quantity of mobile application traffic keeps increasing, operators are facing the scalability limits of VoIP protocols. Higher queuing delays at the Session Initiation Protocol (SIP) server create significantly more retransmissions in the network. When the message arrival rate including retransmissions exceeds the message serving capacity of a SIP server, the queue size increases and eventually the SIP server can crash. Our analysis demonstrates that server crash can be prevented if the buffer size of the SIP server is limited. However, having smaller buffer sizes yields side effects such as lower successful transaction ratio for bursty traffic. In this paper, we propose a new SIP server scheduling mechanism in which the original incoming SIP requests have strict priority over the retransmitted requests. The priority based scheduling mechanism provides network administrator with the ability to configure the buffer size of a SIP server to a moderately high value. We implement the proposed priority-based scheduling mechanism in the JAIN-SIP stack and confirm that the implementation requires minimal changes to the SIP standard. Numerical experiments show that the proposed scheduling mechanism provides significantly and consistently better scalability at high buffer sizes compared to the heavily used first-in-first-out scheduling, thus enabling us to avoid server overloads.

In the Identity-Based Encryption (IBE) setting, the rejoin functionality seems to be impossible since each user has the unique identity as its public key. Moreover, sometimes these identities are unchangeable, e.g., biological information (finger print iris, and so on) is regarded as the identity. Even if changeable value is indicated as an identity, e.g., e-mail address, it is preferable that the same identity can be used after a secret key is leaked. In this paper, we give a formal security definition of RIBE with the rejoin functionality, and also show that the Seo-Emura RIBE scheme [PKC 2013] (with a slight modification) has the rejoin functionality.

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Scalable Video Coding (SVC) is an extension of H.264/AVC, aiming to provide the ability to adapt to heterogeneous networks or requirements. It offers great flexibility for bitstream adaptation in multi-point applications such as videoconferencing. However, transcoding between SVC and AVC is necessary due to the existence of legacy AVC-based systems. The straightforward re-encoding method requires great computational cost, and delay-sensitive applications like videoconferencing require much faster transcoding scheme. This paper proposes a 3-stage fast SVC-to-AVC transcoder with medium-grain quality scalability (MGS) for videoconferencing applications. Hierarchical-P structured SVC bitstream is transcoded into IPPP structured AVC bitstream with multiple reference frames. In the first stage, mode decision is accelerated by proposed SVC-to-AVC mode mapping scheme. In the second stage, INTER motion estimation is accelerated by an optimized motion vector (MV) conjunction method to predict the MV with a reduced search range. In the last stage, hadamard-based all zero block (AZB) detection is utilized for early termination. Simulation results show that proposed transcoder achieves very similar coding efficiency to the optimal result, but with averagely 89.6% computational time saving.