Abstract
One method to create a high-performance computer is to use parallel processing to connect multiple computers. The structure of the parallel processing system is represented as an interconnection network. Traditionally, the communication links that connect the nodes in the interconnection network use electricity. With the advent of optical communication, however, optical transpose interconnection system networks have emerged, which combine the advantages of electronic communication and optical communication. Optical transpose interconnection system networks use electronic communication for relatively short distances and optical communication for long distances. Regardless of whether the interconnection network uses electronic communication or optical communication, network cost is an important factor among the various measures used for the evaluation of networks. In this article, we first propose a novel optical transpose interconnection system–Petersen-star network with a small network cost and analyze its basic topological properties. Optical transpose interconnection system–Petersen-star network is an undirected graph where the factor graph is Petersen-star network. OTIS–PSN
Keywords
Introduction
Computing performance largely depends on processor speed and memory capacity. Parallel processing, which connects multiple processors, has emerged because improvements in the physical performance of processors and memory have relatively slowed down in recent years. For an interconnection network, the connection structure of the parallel processing system is represented on a topology. The interconnection network is represented as a graph mapping the processors as nodes and the communication links that connect the processors as edges. 1
Designing a good interconnection network is the same as creating a good parallel processing system. The interconnection networks that have been reported so far can be largely classified into mesh, torus, hypercube, and start graph classes. The hypercube class has been commercialized as iPSC/2, iPSC/860, and n-CUBE/2; the mesh class as MasPar Intel Paragon, XP/S, Touchstone DELTA System, and Mosaic C; and the three-dimensional mesh class as Cray T3D, MIT’s J-Machine, and Tera Computer. 2
In the systems mentioned in the preceding paragraph, electronic signals are transmitted along the communication links. After the emergence of optical communication, an optical transpose interconnection system (OTIS), which combines the advantages of both electronic communication and optical communication, was proposed by Marsden et al. 3 The OTIS network is implemented using free-space optoelectronic technology. In terms of transmission speed, power consumption, and error rate, the breakeven point for optical communication occurs when the length of the communication link is less than 1 cm. However, the installation cost is inexpensive for electronic communication. 4
In OTIS,
In a graph, the number of edges connected to a certain node is called the degree of the node, and the number of edges existing on the shortest path between two different nodes is called the distance. The degree of the graph is the maximum value among the degrees of all nodes. The diameter of the graph is the maximum value among the distances between arbitrary nodes. An important measure for evaluating interconnection networks is network cost, which can be calculated as the degree × diameter. Because degree refers to the number of communication links, the hardware installation cost increases when the degree increases. The diameter represents the length of the message transfer path between two processors, and when the diameter increases, the message transfer time increases, thus affecting the software cost. Thus, network cost is an important measure for the evaluation of interconnection networks. 16
In this article, we propose an optical transpose interconnection system–Petersen-star network (OTIS–PSN) designed using a Petersen-star network (PSN), which has a small network cost. Section “OTIS, Petersen graph, and PSN” describes the basic concept of OTIS, the Petersen graph, and the PSN. Section “OTIS–PSN” defines the OTIS–PSN, analyzes its basic properties, and compares the network cost with other OTIS networks. Section “Communication algorithm” presents the routing and broadcasting algorithms for OTIS–PSN. Finally, section “Conclusion” concludes this article.
OTIS, Petersen graph, and PSN
OTIS
A basic graph that constitutes OTIS is called a factor graph (hereinafter referred to as factor). An OTIS consists of
OTIS networks are designed based on the OTIS rule (the
The address of node

OTIS-Q2. 8
In OTIS, the number of groups is exactly the same as the number of nodes of the factor. Suppose that the number of nodes in the factor is
The outline of OTIS routing is as follows. The starting node is
Petersen graph
The Petersen graph consists of 10 nodes and 15 edges. It has the best network cost among graphs with 10 nodes, and has a degree of 3 with a diameter of 2. Figure 2 shows the Petersen graph. The number on the left in the node address is smaller than the number on the right. 22

Petersen graph and spanning tree: (a) the Petersen graph and (b) spanning tree. 2
In a Petersen graph,
For the all-port model, the one-to-all broadcasting in the Petersen graph is edge-disjoint and broadcasting time is 2. Initially, node 12 has a message. As presented in Figure 2(b), the broadcasting algorithm given in Algorithm 2 is applied.
Because the Petersen graph is a node (edge)-symmetric graph, Algorithm 2 is valid even though any arbitrary node can have a message initially.
PSN
The PSN uses the Petersen graph as the basic module. The number of internal edges that are connected to one node is three and the number of external edges is
PSN
The edges of PSN
where 2 <
In Figure 3, the numbers in black are

Two-level Petersen-star PSN2. 23
It is assumed that in PSN
The time complexity of Algorithm 3 is as follows. In terms of the worst case in each line, the time complexity is 2 in lines 2 and 5, and 1 in line 3. Therefore, the time complexity is (
OTIS–PSN
Definition
OTIS–PSN
The edges in OTIS–PSN
Figure 4 shows OTIS–PSN2 with the factor PSN2. Each group is represented by a blue circle, and the group address is expressed as an orange four-digit number on the circle. OTIS–PSN2 consists of 102 groups. One group is shown in detail on the left. Only selected groups (out of 99) are shown on the right to limit the complexity of the diagram. Orange lines represent the o-edges, and black lines represent the e-edges. Again, only certain edges are shown to limit complexity.

OTIS–PSN2 showing factor PSN2 (left) and the remaining 99 groups (right).
For example, let us look at node <1212, 1234 > in Figure 4 (left). <1212, 1234> is connected to <1234, 1212> by an o-edge and connected to <1212, 1212>, <1212, 1225>, <1212, 1215>, and <1212, 3412> by e-edges. Let us examine the nodes connected to node <1212, 1234> by e-edges. Node <1212, 3412> is connected by an external edge, and the remaining three nodes are connected by internal edges. In Figure 4 (left), which is a group, 99 nodes excluding node <1212, 1212> are all connected to nodes belonging to other groups. Similarly, nodes <
Topological properties of OTIS–PSN
In this section, the basic topological properties of OTIS–PSN are examined. The number of nodes in OTIS–PSN
Theorem 1
The total number of nodes in OTIS–PSN
Proof
The factor of OTIS–PSN
The degree of an arbitrary node is the number of edges incident to that node, and the degree of the graph is the maximum value among the degrees of all nodes. The degree of OTIS–PSN
Theorem 2
The degree of OTIS–PSN
Proof
The degree of PSN
In a graph, a path is a node sequence that connects one node to another node, and distance is the number of edges on that path. Between two arbitrary nodes, the minimum distance is
Theorem 3
The diameter of OTIS–PSN
Proof
Suppose that two arbitrary nodes are
Network cost is an important measure for the evaluation of a network. Table 1 shows the network cost of OTIS–PSN versus various OTIS networks. For ease of understanding, we compare network costs per node, as
Comparison of network cost with other OTIS networks.
As shown in Table 1, because
Network cost by number of nodes.
OTIS: optical transpose interconnection system.
Theorem 4
OTIS–PSN
Proof
First, it should be determined whether PSN
Communication algorithm
Routing algorithm
The routing path between two nodes is the message delivery path. A path is a node sequence connected by an edge. In OTIS–PSN
Because the worst-case time complexity of Algorithm 3 is 3
Broadcasting algorithm
Routing transfers a message from the node that has the message to another node. In contrast, broadcasting sends a message to every node in the network. Broadcasting is performed by successive calling to transmit a message and has several limitations: first, only two nodes participate in a call; second, a call is completed in a unit time; third, each node may take part in only one call in a unit time; and fourth, a call appears only between two neighboring nodes. 24 In one-to-all broadcasting, the originating node sends the message to all nodes, whereas in all-to-all broadcasting, each node has a different message, which it sends to all nodes. Here, we use one-to-all broadcasting. The one-port model allows a node to send a message to only one other node in a unit of time, whereas the multi-port model allows a node to send a message to multiple nodes. Here, we deal with the all-port model, which allows a message to be sent to all nodes in the same unit time.
The following is a brief overview of the broadcasting algorithm:
Stage 1. The message is sent to all nodes of the factor graph
Stage 2. The message is transmitted to all the nodes that are connected to the nodes of
Stage 3. In each group, Stage 1 is performed to simultaneously deliver the message to all nodes in the same group.
Next, to better understand the broadcasting algorithm, the broadcasting in OTIS–PSN2 is examined. The node that initially had the message is called
Stage 2 is simple. A node set <1234,
Theorem 5
In OTIS–PSN
Proof
The time complexity of broadcasting Algorithm 2 is calculated. In Steps 1.1 and 1.3, the message is sent to 10 nodes of the Petersen graph to which it belongs, in only two times, according to broadcasting Algorithm 1. Step 1.2 is performed once. In Step 1.4, Steps 1.2 and 1.3 are repeated (
Conclusion
In this article, we proposed an OTIS–PSN that has a small network cost and analyzed its basic topological properties. We then compared the network cost of previously reported OTIS networks with the proposed OTIS network (OTIS–PSN). OTIS–PSN
Footnotes
Handling Editor: Dr Yanjiao Chen
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (no. 2020R1A2C1012363).
