Distributed Internet of Things (Distributed IoT) is a large-scale, heterogeneous, dynamic distributed architecture environment which is gradually formed based on Internet of Things (IoT) technology. In order to cope with the large number access requirements for IoT data brought by application expansion, the data of IoT devices are usually stored in the management server (DMS) of current domain, and adopt a centralized access control mechanism to user. This centrally approach can easily cause data to be tampered with and leaked. Moreover, registering different identities when user accesses different domains increases the difficulty to manage his identities. Therefore, this paper proposes a blockchain-based access control scheme called BacS for Distributed IoT. In BacS, firstly, we use account address of the node in blockchain as the identity to access DMS, redefine the access control permission of data of devices and store on blockchain. Then we design processes of authorization, authorization revocation, access control and audit in BacS. Finally, we use a lightweight symmetric encryption algorithm (SEA) to achieve privacy-preserving for Distributed IoT system. We build a credible experimental model on Ethereum private chain, results show that BacS is feasible and effective that it can achieve secure access in Distributed IoT environment while protecting privacy.

Distributed Constraint Optimization Problem (DCOP) is a promising framework for modeling a wide variety of multi-agent coordination problems. Best-First search (BFS) and Depth-First search (DFS) are two main search strategies used for search-based complete DCOP algorithms. Unfortunately, BFS often has to deal with a large number of solution reconstructions whereas DFS is unable to promptly prune sub-optimal branch. However, their weaknesses will be remedied if the two search strategies are combined based on agents’ positions in a pseudo-tree. Therefore, a hybrid DCOP algorithm with the combination of BFS and DFS, called BD-ADOPT, is proposed, in which a layering boundary is introduced to divide all agents into BFS-based agents and DFS-based agents. Furthermore, this paper gives a rule to find a suitable layering boundary with a new strategy for the agents near the boundary to realize the seamless joint between BFS and DFS strategies. Detailed experimental results show that BD-ADOPT outperforms some famous search-based complete DCOP algorithms on the benchmark problems.

ADOPT and BnB-ADOPT are the two important search-based complete algorithms to solve Distributed Constraint Optimization Problem (DCOP). However, a large number of solution reconstructions appear in ADOPT and sub-optimal branch can’t be promptly pruned in BnB-ADOPT. A layering DCOP algorithm to combine ADOPT and BnB-ADOPT is proposed to remedy their weakness, named Layering-ADOPT. In Layering- ADOPT, a layering boundary is introduced to divide all agents into two classes, one performing ADOPT and another for BnB-ADOPT. This paper presents a rule to get a layering boundary and a new strategy to realize the joint between ADOPT and BnB-ADOPT. In the experiment, Layering-ADOPT and ADOPT as well as BnB-ADOPT are compared on random DCOPs. The results show that Layering-ADOPT is superior to ADOPT and BnB-ADOPT on the test problems.

Depth First Search (DFS) pseudo-tree is popularly used as the communication structure in complete algorithms for solving Distributed Constraint Optimization Problems (DCOPs) from multiagent systems. The advantage of a DFS pseudo-tree lies in its parallelism derived from pseudo-tree branches because the nodes in different branches are relatively independent and can compute concurrently. However, the constructed DFS pseudo-trees in experiments often come to be chain-like and greatly impair the performances of solving algorithms. Therefore, we propose a new DPOP algorithm using a Breadth First Search (BFS) pseudo-tree as the communication structure, named BFSDPOP. Compared with a DFS pseudo-tree, a BFS pseudo-tree is more excellent on the parallelism as it has much more branches. Another notable advantage is that the height of a BFS pseudo-tree is much lower than that of a DFS pseudo-tree, which gives rise to the shorter communication paths and less communication time. The method of Cluster Removing is also presented to allocate cross-edge constraints to reduce the size of the largest message in BFSDPOP. In the experiment, BFSDPOP with a BFS pseudo-tree and original DPOP with a DFS pseudo-tree are compared on three types of problems - graph coloring problems, meeting scheduling problems and random DCOPs. The results show that BFSDPOP outperforms original DPOP in most cases, which proves the excellent attributes of BFS pseudo-tree over DFS pseudo-tree.