New services can use fog nodes to distribute Internet of Things (IoT) data. To distribute IoT data, we apply the publish/subscribe messaging model to a fog computing system. A service provider assigns a unique identifier, called a Tag ID, to a player who owes data. A Tag ID matches multiple IDs and resolves the naming rule for data acquisition. However, when users configure their fog node and distribute IoT data to multiple players, the distributed data may contain private information. We propose a table-based access control list (ACL) to manage data transmission permissions to address this issue. It is possible to avoid unnecessary transmission of private data by using a table-based ACL. Furthermore, because there are fewer data transmissions, table-based ACL reduces traffic. Consequently, the overall system's average processing delay time can be reduced. The proposed method's performance was confirmed by simulation results. Table-based ACL, particularly, could reduce processing delay time by approximately 25% under certain conditions. We also concentrated on system security. The proposed method was used, and a qualitative evaluation was performed to demonstrate that security is guaranteed.

MQTT is one of the promising protocols for various data exchange in IoT environments. Typically, those environments have a characteristic called “edge-heavy”, which means that things at the network edge generate a massive volume of data with high locality. For handling such edge-heavy data, an architecture of placing multiple MQTT brokers at the network edges and making them cooperate with each other is quite effective. It can provide higher throughput and lower latency, as well as reducing consumption of cloud resources. However, under this kind of architecture, heterogeneity could be a vital issue. Namely, an appropriate product of MQTT broker could vary according to the different environment of each network edge, even though different products are hard to cooperate due to the MQTT specification providing no interoperability between brokers. In this paper, we propose Interworking Layer of Distributed MQTT brokers (ILDM), which enables arbitrary kinds of MQTT brokers to cooperate with each other. ILDM, designed as a generic mechanism independent of any specific cooperation algorithm, provides APIs to facilitate development of a variety of algorithms. By using the APIs, we also present two basic cooperation algorithms. To evaluate the usefulness of ILDM, we introduce a benchmark system which can be used for both a single broker and multiple brokers. Experimental results show that the throughput of five brokers running together by ILDM is improved 4.3 times at maximum than that of a single broker.

Source routing multicast has been gathering much more attention rather than traditional IP multicast, since it is thought to be more scalable in terms of the number of groups at the cost of higher traffic loads. This paper introduces a mathematical framework to analyze the scalability of source routing multicast and IP multicast by leveraging previous multicast studies. We first analyze the amount of data traffic based on the small-world nature of networks, and show that source routing multicast can be as efficient as IP multicast if a simple header fragmentation technique (subgrouping) is utilized. We also analyze scalability in terms of group numbers, which are derived under the equal budget assumption. Our analysis shows that source routing multicast is competitive for low bit-rate streams, like those in the publish/subscribe service, but we find some factors that offset the advantage. This is the first work to analytically investigate the scalability of source routing multicast.

Resource discovery is an essential function for distributed mobile applications integrated in vehicular communication systems. Key requirements of the mobile resource discovery are wide-area geographic-based discovery and scalable resource discovery not only inside a vehicular ad-hoc network but also through the Internet. While a number of resource discovery solutions have been proposed, most of them have focused on specific scale of network. Furthermore, managing a large number of mobile resources in the Internet raises a scalability issue due to the mobility of vehicles. In this paper, we design a solution to wide area geographical mobile resource discovery in heterogeneous networks composed of numerous mobile networks possibly connected to the Internet. The proposed system relies on a hierarchical publish-subscribe architecture and geographic routing so that users can locate resources according to geographical coordinates without scalability issue. Furthermore we propose a location management mechanism for mobile resources, which enables to reduce periodic updates of geographical location. Numerical analysis and simulation results show that our system can discover mobile resources without overloading both mobile network and the Internet.

The management of subscriptions and events is an important task in the content-based publish/subscribe system. A good management mechanism can not only produce lower matching costs to speed up the delivery of matched events to the interested subscribers but can also induce good load balancing for subscription storage. In this paper, we consider the construction of this kind of system over a peer-to-peer overlay network and propose two message-to-node mapping schemes for system management. We both analyze and simulate the performance of the proposed schemes. The simulation results show the superiority of our schemes over existing ones.

Content-based publish/subscribe systems provide a useful alternative to traditional address-based communication due to their ability to decouple communication between participants. It has remained a challenge to design a scalable overlay supporting the complexity of content-based networks, while satisfying the desirable properties large distributed systems should have. This paper presents the design of Mirinae, a new structured peer-to-peer overlay mesh based on the interests of peers. Given an event, Mirinae provides a flexible and efficient dissemination tree minimizing the participation of non-matching nodes. We also present a novel ID space transformation mechanism for balancing routing load of peers even with highly skewed data, which is typical of the real world. Our evaluation demonstrates that Mirinae is able to achieve its goals of scalability, efficiency, and near-uniform load balancing. Mirinae can be used as a substrate for content-search and range query in other important distributed applications.