MQTT is a widely used protocol in IoT systems. Due to the central role of an MQTT broker in handling messages, large-scale systems need to distribute the load across multiple brokers. When using multiple brokers, sharing subscription topics among them is a common strategy to prevent message flooding. Given the potentially large volume of topics, some existing approaches use a Bloom filter to store and manage them with space-saving. However, these methods have difficulties in managing wildcards, i.e., many queries to the Bloom filter could occur to search one topic. In this paper, we introduce a method to handle wildcard topics efficiently using a Bloom filter. The proposed method adds prefixes of subscription topics to the Bloom filter. Searching for a published topic is processed like using Trie structure while considering wildcard patterns. Experimental results demonstrate that our method reduces the number of queries to the Bloom filter compared to existing methods in many cases.

MANET operates autonomously without central-ized administration, which poses the risk of malicious behavior by sinister nodes. Address duplication detection, in particular, is an inevitable function of network operation and requires legitimacy in its results. In this paper, we propose a method using blockchain in MANET to ensure the legitimacy of address information. To evaluate the effectiveness of our approach, we measured address duplication detection times and found that while blockchain implementation added some overhead, it significantly reduced detection times compared to an existing method.

In a huge earthquake, disaster notification system may cease to function due to the damage of communication cables, etc. Therefore, in this study, we assume a wireless mesh network using LPWA that operates independently from existing infrastructures such as the Internet. Disaster notification to first responders must be delivered reliably and with low latency. Flooding is a possible way to obtain redundancy. However, flooding increases the number of messages, and there is concern that increased latency due to time slot control. In this study, we focus on Plumtree that is a fault-tolerant and message-reducing algorithm and consider its application to the disaster notification wireless mesh network. Specifically, we propose a method to enable unicast notification to the first responder node by extending Plumtree. In the proposed method, each node has an additional routing table to keep the direction of the first responder node. Experimental results show that the number of hops in the proposed method is sufficiently small for message loss rates up to 5 %. Even when the loss rate is 50 %, the number of hops is less than approximately two and a half times compared to the shortest path tree.

One of the protocols gaining popularity for Internet of Things (IoT) systems is MQTT. It is lightweight and has loose coupling nature derived from the publish/subscribe communication model. The capability of handling heterogeneous data is crucial in supporting cooperation among various applications and sensors. In this study, we evaluate the performance of MQTT communication with the combination of different payload sizes. Experimental result shows different tendencies of the hetero data capability by broker products.

A blockchain network simulator SimBlock was developed to enable large-scale blockchain researches. Since it was released in June 2019, it has facilitated number of studies on blockchain performance and security. We demonstrate how such a simulator enables blockchain studies by showing experiments running on SimBlock.

YouTube is a online video sharing service that is that many people view. If we can know the emotions of video viewers, we can use them to improve usability. In this study, we propose two method for estimating the emotion of YouTube videos from the comments of each video: a BERT-based method and a rule-based method. For the former, we use BERT with fine-turning by 350 video comments to estimate the emotion. In the rule-based method, emotion values are calculated using a Japanese emotional expression dictionary. To evaluate these methods, we obtained emotion values from 100 respondents who were asked to fill out questionnaires as ground truth. The results of the evaluation using cosine similarity showed that BERT-method was able to estimate emotions with higher accuracy than the rule-based method.

In Japan, the declining birthrate and aging population have become a social problem, and it is predicted that the number of elderly people will reach about 40 million in 2040. As a result, the number of dementia patients is expected to increase. There are four major dementias, and appropriate care methods are different for each. In addition, early detection is important to suppress symptoms. Therefore, there is a need for a means to easily determine the type of dementia. In this study, we propose an automatic classification method for four major dementias. Using crowdsourcing, we extract text data of four major dementia symptoms from Twitter. By fine-tuning BERT with them, we obtain a classifier. Experimental result shows that the proposed method provides higher accuracy than random classification.

MQTT is a simple message protocol with the publish/subscribe model, which enables loosely coupled communication. In large-scale systems, load balancing is required because of the problem of concentrated load on brokers and subscrebers. However, existing load balancing methods have difficulty in distributing the load according to the load status of broker and the sending frequency of publisher, and there is a problem of a single point of failure. In this study, we propose a load balancing method using server redirection specified in MQTT v5.0 to improve the problems of existing methods. In order to verify the effectiveness of the proposed method, we conducted comparison experiments with DNS round-robin, an existing method, and measured the throughput and CPU utilization of each broker as evaluation indices.

Sensor networks to autonomously collect data and send it to the cloud via gateways are expecting for providing various IoT services. In many cases, the service providers need to build their own sensor network and many sensors to measure same data will place in a narrow area. To solve this problem, we have proposed an Information-Centric Networking based wireless Sensor Network (ICSN) to provide multiple IoT services. Also, we have proposed an ICSN Platform (ICSNP) that provides the functions of executing IoT services in sink nodes. However, the number of requests increases due to increasing number of services simultaneously at the sink node. It causes performance degradation due to rising processing load. Therefore, we have proposed the cloud-based load distribution model for application to an environment of multiple IoT services. In this paper, we evaluated the node load focusing on the sensor data acquisition interval by implementing the proposed model. As a result, the proposed method can reduce the load on the sink node compared to the conventional method even in an environment with many concurrently connected applications and short sensor data acquisition intervals. Therefore, the relationship between the acquisition interval and load in actual operation are indicated.

Skip Graph is a structured overlay that preserves the order of keys and provides efficient routing, especially for complex queries such as range queries. However, existing routing methods for range queries in Skip Graph have problems such as long path lengths and a large number of messages because of inefficiencies. In this paper, we propose a new routing method for range queries named Detouring Range Search (DRS), that provides more efficient routing by utilizing detour routes. In the proposed method, each node that receives a query divides the target range into subranges based on the center of the subordinate node sequence and delegates them to its neighbor nodes. Our evaluation experiments show that the proposed method can reduce the average path length by approximately 20% compared with that of an existing method when the number of nodes is sufficiently large.

MQTT is one of the best-known communication protocols for the Internet of Things (IoI). Its light-weight design and loose-coupling nature by publish/subscribe messaging model enable effective information exchange among various devices. Since MQTT brokers could be performance bottlenecks due to the massive amount of data from the increasing loT devices, their performance holds interest from researchers and engineers. Furthermore, the performance characteristics of MQTT version 5.0, which was released in 2019 and accompanied by new functionalities e.g., shared-subscription, have not become clear. To provide a way to measure MQTT broker performance efficiently and accurately, we have developed an open-source load testing tool MQTTLoader. In this demonstration, we introduce MQTTLoader with its capabilities and features. We also show how it works by using our demonstration environment and describe some results of benchmarking MQTT brokers.

Skip Graph, one of the structured overlays, provides a scalable network owing to the routing path lengths of O (log n), where$n$denotes the total number of nodes. However, there is a problem that most of the routing paths are quite longer than the shortest paths because each node in the network knows only its neighbors, rather than the global topology. In general, long routing paths lead to long delay times and low fault tolerance. Herein, we propose Detouring Skip Graph, which shortens the path lengths through the use of detour routes. It does not require construction of extra links or modification of its topology; thereby, it can succeed in shortening them while maintaining the advantages of Skip Graph. The evaluation experiments show that the average path length was shortened by approximately 20%-30% in comparison with Skip Graph.

Publish/subscribe is a communication model for exchanging messages via a broker while providing loose coupling. So far, several studies have been conducted to address load concentration on the broker by forming distributed brokers. However, although they achieve higher throughput by load distribution among multiple brokers, these existing studies require an increased latency for message delivery. In this paper, we propose a novel method to construct and maintain an adaptive topology that features both scalability and immediacy in distributed publish/subscribe messaging. The proposed method is for topic-based publish/subscribe systems and uses a number of brokers to form an overlay network. Its topology changes dynamically to compose a subgraph for each topic in a single-hop or multi-hop manner according to the topic load (i.e., the number of clients). The experimental results show that compared to existing studies, the proposed method reduces the delivery path length, which is a principal factor that affects latency. Especially for low load topics, the reduction rate of the proposed method reaches values greater than 60%.

Improving transaction throughput is an important challenge for Bitcoin. However, shortening the block generation interval or increasing the block size to improve throughput makes it sharing blocks within the network slower and increases the number of orphan blocks. Consequently, the security of the blockchain is sacrificed. To mitigate this, it is necessary to reduce the block propagation delay. Because of the contribution of new Bitcoin protocols and the improvements of the Internet, the block propagation delay in the Bitcoin network has been shortened in recent years. In this study, we identify impacts of compact block relay—an up-to-date Bitcoin protocol—and Internet improvement on the block propagation delay and fork rate in the Bitcoin network from 2015 to 2019. Existing measurement studies could not identify them but our simulation enables it. The experimental results reveal that compact block relay contributes to shortening the block propagation delay more than Internet improvements. The block propagation delay is reduced by 64.5% for the 50th percentile and 63.7% for the 90th percentile due to Internet improvements, and by 90.1% for the 50th percentile and by 87.6% for the 90th percentile due to compact block relay.

In Bitcoin and Ethereum, nodes require large storage capacity to maintain all the blockchain data, such as transactions, UTXOs, and account states. As of May 2020, the storage size of the Bitcoin blockchain has expanded to 270 GB, and it will continue to increase. This storage requirement is a major hurdle to becoming a block proposer or validator. Although many studies have attempted to reduce the storage size, in the proposed methods, a node cannot keep all blocks or cannot generate a block. We propose an architecture called Trail that allows nodes to hold all blocks in a small storage and to generate and validate blocks and transactions. Trail does not depend on a consensus algorithm or fork choice rule. In this architecture, a client who issues transactions has the data to prove its own balances and can generate a transaction containing the proof of balances. The nodes in Trail do not store transactions, UTXOs and account balances: they keep only blocks. The blocksize is approximately 8 KB, which is 100 times smaller than that of Bitcoin. Further, the block size is constant regardless of the number of accounts and the number of transactions. Compared to traditional blockchains, clients who issue transactions must store additional data. However, we show that proper data archiving can keep the account device storage size small. Trail allows more users to be block proposers and validators and improves the decentralization of the blockchain.

In Skip Graph, a structured overlay, each node constructs its routing table by choosing connected nodes based on its membership vector. However, membership vectors are determined randomly; therefore, nodes do not always form an ideal topology. This can cause the route length to be long. Therefore, we propose Self-Refining Skip Graph, a structured overlay where each node refines its routing table toward an ideal Skip Graph topology. Our proposed method has shorter route length as approaching to an ideal topology while maintaining the robustness derived from the mechanism of membership vectors. Our evaluation confirms that the topology approaches to an ideal one and that the route length becomes shorter than that in Skip Graph.

Structured overlays enable a number of nodes to construct a logical network autonomously and search each other. Skip Graph, one of the structured overlays, constructs an overlay network based on Skip List structure and supports range queries for keys. Skip Graph manages routing tables based on random digits; therefore, the deviation of them disturbs effective utilization of the routing table entries and increases path length than the ideal value. We therefore propose FRT-Skip Graph, a novel structured overlay that solves the issues of Skip Graph and provides desirable features not in Skip Graph. FRT-Skip Graph is designed based on Flexible Routing Tables and supports range queries similarly to Skip Graph. Furthermore, it provides features derived from FRT, namely, dynamic routing table size and high extensibility.

Scalable messaging methods for IoT services are needed to accommodate a vast number of devices. Skip Graph based topic based pub/sub (SG-TPS), which utilizes multiple brokers composing a structured overlay network, is one of the promising candidates. In SG-TPS, the distribution delay time is widely influenced by a way to assign subscribers to each broker. There are two possible approaches: the intensive assignment by which subscribers having a same topic are accommodated on a same broker, and the extensive assignment by which the subscribers are accommodated on different brokers as far as possible. In this paper, we formulate the difference of the distribution delay time between these two approaches, and discuss about the optimization of subscriber assignment.

Pub/Sub communication model becomes a basis of various applications, e.g. IoT/M2M, SNS. These application domains require new properties of the Pub/Sub infrastructure, for example, supporting a large number of devices with widely distributed manner, handling emergency messaging with priority control and so on. In order to meet the demands, we proposed Software Defined Network Aware Pub/Sub (SAPS) which utilize the both Application Layer Multicast (ALM) and SDN, especially Open Flow based multicast (OFM). A simulation was done for evaluating the hybrid architecture in traffic and transmission delay reduction, and then the issues to be solved in the current design were discussed.

Topic-based pub/sub (TBPS) messaging plays an important role in building event-driven Internet of Things (IoT) applications. In IoT applications, scalability and locality-awareness are important properties that help to achieve low-latency message delivery and efficient usage of network resources. However, none of the existing distributed TBPS methods can simultaneously achieve a sufficient level of both properties. This paper proposes a new TBPS overlay method called 'Skip Graph-based TBPS with Locality-Awareness' (STLA), which extends existing Skip Graph-based TBPS messaging by adding locality- awareness. STLA determines the order of the keys on a Skip Graph overlay network according to the network hierarchy structure using 'locality-aware topic keys' (LATK). Using 'split-forward broadcasting' (SFB) with LATK, the locality-awareness can be dramatically improved. Simulation results show that our method can achieve locality-awareness and reduce the average latency of message delivery for 100,000 subscribers by 76% compared with existing methods. In addition, we have conducted experiments on real distributed data centers using an STLA prototype system, and have confirmed the practicality and feasibility of the proposed method.

Distributed pub/sub messaging has become indispensable for event-driven systems. There are methods for achieving high scalability regarding topic-based pub/sub by using structured overlay networks. However, these methods waste network resources concerning "exhaust data," which have low or no value most of the time. There are at least two problems: each publisher node continues to forward data to a relay node even if there are no subscribers, and multicast trees are constructed which are excessively large for low value data, namely having a small number of subscribers. In this paper, we formulate the requirements of overlay networks by defining a property called "strong relay-free" as an expansion of relay-free property, and propose a practical method satisfying the property by using Skip Graph. The proposed method involves publishers and subscribers composing connected sub graphs to enable detecting the absence of subscribers and autonomously adjusting the tree size. Through simulation experiments, we confirmed that the proposed method can suspend publishing adaptively, and shorten the path length on multicast trees by more than 75% under an experimental condition with 100,000 nodes. The proposed method is competent for decentralized event-driven systems with encouraging the locally produced data to be consumed locally.