Chapter 4. Network Topology Design
4.1. Considerations of Network Topology Design
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Chapter 4. Network Topology Design
4.1. Considerations of Network Topology Design
In CCN, most disconnected base stations require multiple hops to connect to the core network. The network topology of CCN may have a great impact on the efficiency of CCN, which is the efficiency of disaster response operation and its stability. The objective of network topology design is to find a network topology to maximum the disaster response efficiency. The evaluation factors of disaster response efficiency include the emergency level of the afflicted areas or the level of the disaster and the number of disaster responders and victims. Referring to Fig. 4.1., the CCN network topology should deploy to those incident areas that have large population or high emergency level to maximum the disaster response efficiency. However, some important areas, such as command centers, require higher reliability and network bandwidth. These two requirements, maximization of the disaster response efficiency and reliability, are dependent to each other. A good network topology design algorithm of CCN should compromise these two requirements.
Besides, there are some constraints needed to be considered. The number of CRPs and the number of antennas in each CRP are fixed. Hence, the number of selected BSs is constrained by the number of CRPs; the number of selected links of each selected BS cannot exceed the number of antennas in each CRP. The packages are forwarded through multi-hop, too many hops may cause long delay time and consume too much intra-BS bandwidth. Therefore, the number of hops from some important areas to the core network should be limited to maintain appropriate quality of network service.
Except these basic constraints mentioned above, CCN topology design need to be considerate
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of more complicated problems. These problems are discussed as fellows.
Figure 4.1. Considerations of topoloy design
Tree-type Topology vs. Mesh Network Topology
Strengths of the tree-type network topology are easy to construct and maintain, and thus tree-type network topology is wildly applied. But, it is vulnerable to a single link or node failure. The mesh network topology increases the network availability by using multiple path to connect the core network and critical areas, such as command centers, such that every critical areas can reach the core network via two or more disjointed paths. However, it will have a side effect to the total profit when using multiple path. Hence, it needs to balance the network availability and total profit when employing multiple path.
Population
Candidate link
selected link Command center
Isolated BS Selected BS
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Single Operator vs. Multiple Operators
In general, the coverage areas of base stations are well planned and mutual exclusive.
Therefore, it’s simpler to construct CCN network by using base stations from one operator than multiple operators. Nevertheless, enlarging the concurrent users of some critical areas may increase the disaster response efficiency. This can be achieved by including the base stations from multiple operators in the same covered area into CCN. However, the profit function of the base stations that cover the same area is a decreasing function of the number of base stations in service. The marginal benefit of profits will gradually decease when multiple base stations covering the same area are selected into CCN.
Depth Bound vs. Depth Weight
The base stations connect to the core network by multi-hops in CCN. In order to avoid long hop connection and too much forwarding traffic, the number of hops has to be controlled.
Depth bound constrains the number of hops by setting an upper bound of the number of hops.
This model is simple, but may discard a seriously damaged area that is too far from the root.
Depth weight dynamically adjusts the tree depth so that the serious damage areas would not be discarded by the depth constraint.
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Simple FT Cross FT
MPFN Cross MPFN
Figure 4.2. Four types of CCN network topology design problems
Combinations of these considerations discussed above are simple forwarding tree (Simple FT), cross-forwarding tree (Cross FT), multiple path forwarding network (MPFN) and Cross multiple path forwarding network (Cross MPFN), are proposed and discussed in this dissertation. Examples of these topologies are showed in Fig. 4.2.
Simple FT design problem is to find a K-maximum spanning tree with degree bound. The original base stations of Simple FT belong to one operator. Dash lines denote the selected wireless links. Cross FT is also a tree-type topology. But, the original base stations of Cross FT are from multiple operators. Triangle and rectangle denote the base stations of different
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operator. Cross FT assumes that disaster response authority has the privilege to expropriate any operator’s base stations in an emergency.
MPFN design problem is to find a mesh network topology with degree bound to maximize the disaster response efficiency. Moreover, critical areas must have multiple outgoing paths which represented by the lines with squares to core network. Besides, the lengths of these multiple outgoing paths are limited with a fixed number of hops. The base stations of MPFN are from one operator. Cross MPFN is a mesh network topology, too. Cross MPFN use the base stations from multiple operators.
4.2. Related Works
Most topology design researches aim to find a minimum cost network with reliability constraint. In this section, we will present two models of network topology design problems.
The first model adopt a two-phase methodology to find a mesh network with minimum cost while stratifying reliability; the second model formulates the network topology design problem as a minimum cost mesh network with reliability constraint.
Charnsripinyo [10] proposed a network topology design model that aims to finds a mesh network with minimum constructing cost while meeting reliability. Charnsripinyo adopt a two-phase design methodology. In the first phase, Charnsripinyo models the problem as a minimum cost spanning tree problem and provides a minimum cost network. The problem in the phase two is formulated into a Knapsack problem which aims to maximize the number of rings by augmenting edges to the network topology from the phase one to satisfy the reliability requirement. The experiment results show that this approach can greatly enhance the network reliability and quality of services. However, his model does not clear define the
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relationship between the number of rings and reliability. Therefore, the reliability of the network topology is unpredictable.
Elshqeirat [16] modeled the topology design problem as topology design with minimal cost subject to network reliability constraint. The reliability of the network topology is the probability that at least one spanning tree in the network topology is functional. Elshqeirat also proposed a dynamic programming (DP) scheme and three greedy heuristics algorithms to solve this problem. In Elshqeirat’s model, reliabilities of each nodes is unified that is inapplicable to CCN. CCN topology design aims to find a tree-type or mesh network topology with maximum disaster response efficiency. The reliability requirements of different nodes are variant. Some critical areas request multiple outgoing paths, but some are not.