Design Issues of the CCN

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should fit the national dialing plan to enable users to turn their cell phones into walkie-talkies.

This instruction can also be automatically sent to all cell phones within the CNN covered area by Short Message Service, thereby enabling even trapped victims to receive it. Notably, the scope of this service is confined to each base station to prevent the excessive consumption of resources.

Agency Communication Service: Each group of users with the same functional specialty can form an agency group with a dedicated, easy-to-remember phone number. Thus, every user can make a request to a specific functional agent by dialing the corresponding phone number.

Examples of agency groups are the headquarters, surgical doctors, blood suppliers, medical suppliers, power cutters, and excavators. When a user makes a request by dialing the special phone number, the CCN rings a set number of members of the corresponding group near the caller. Any paged recipient can answer the phone, and the agency database can be preloaded or registered in real time. However, the original phone number of a cell phone may be lost if a CCN does not establish its connection to the core network; thus, the CCN must have its own dialing plan and phone number designation process.

3.6. Design Issues of the CCN

During a real disaster, a CCN may proceed with a phased deployment: disaster assessment, planning, deployment, and operation. Each of these phases presents design concerns, and thus several critical planning and deployment challenges are discussed in this section.

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 Definition of Resource Profit

Resource allocation and scheduling problems are usually modeled as combinatorial optimization problems for which plenty of solutions are available. Some profit is earned when one unit of resource is allocated to a base station, where the objective is to maximize the total profit earned with limited resources. In a CCN design, profit should be measured by the efficiency with which it improves disaster response operations. Moreover, the definition of profit must be defined by a specific disaster response authority, because they possess the relevant real time disaster situation statistics as well as the priority determination authority. A typical profit definition when allocating a CRP to a base station is a linear or nonlinear combination of the emergency level and the user population covered by the base station. The profit definition of allocating a communication channel to a pair of base stations is a major challenge yet to be tackled. In the future, social scientists must formulate improved profit definitions and optimization models.

 Network Topology Design

According to the statistics we collected, more than 3300 base stations crashed during the 88 Flood, which was only a moderate scale disaster affecting a small number of counties in southern Taiwan. However, larger scale system crashes can be anticipated to occur in larger natural disasters. Therefore, the first concern when deploying a CCN is the selection of a limited number of crashed base stations based on the available CRPs as well as the topology for their connectivity; a simple tree-type or a resilient non-tree-type topology can then be formed with the objective of maximizing its efficiency and stability. In our study, the topology design [22,55] was formulated into different combinatorial optimization problems and solved using typical algorithmic methodologies [5]. To maintain the integrity of a CCN and adapt to

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the constant changing conditions of a disaster, the forwarding topology must be replanted frequently. A system that has self-healing capabilities would be preferable, but requires further research.

Tree topology is simple, but also vulnerable to a single link or node failure. In response, Charnrsriponyo [10,11] improved network reliability by maximizing the number of chains, and Elshqeirat [15,16] used a dynamic programming scheme to generate a topology comprising a selected sequence of spanning trees, thereby satisfying a predefined reliability.

All nodes in the methodologies of Charnrsriponyo [10,11] and Elshqeirat [15,16] are identical.

However, some pivot nodes such as command centers require higher bandwidth and reliability than others. Hence, we proposed a better optimization model with differentiated reliability demands together with a Disjoint K-Path Max-Profit Mesh algorithm [22] to satisfy bandwidth and reliability requirements by providing multiple path to the pivot nodes; thus, every pivot node can reach the core network through two or more disjointed paths.

 Deployment Scheduling

Some number of CRPs can be previously stored in the national disaster response center and be transported via some transportation vehicle such as helicopter to the selected stations to construct a CCN rapidly. The deployment sequence may have a big impact on the disaster response efficiency since the profit of restoring a base station keeps decreasing over time. The time variant survival rate, the difficulty of accessing, the delivery time, the topology constraints, and many other parameters all together makes the deployment scheduling a highly complex problem.

Since the transportation capacity may be very limited, it may need several rounds of deployments. Unfortunately, the benefit of saving a station is gradually attenuated with time.

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The deployment sequence will largely determine the disaster response efficiency. A good sequence may save more lives than a bad one. The transport sequence has not only to consider the emergency level of base stations but also to follow the scheduling constraint that ancestor nodes have to be recovered before their child. That’s because a child node cannot connect to the core network without the forwarding of its ancestors.

CCN deployment scheduling problem is similar to fleet routing and scheduling problems [17]

which aim to find an optimal route of one or more vehicles through a graph and assign vehicles to ideal routes at the particular time. Formulations of flee routing and scheduling problems are usually based on multi-commodity network flow problem or vehicle routing problem. Objectives of these formulas are minimizing the unsatisfied demand or maximizing the demand satisfied. Formulas and solutions are proposed in [2,17,22]. Objectives of these researches aim to minimize the transport time and the number of vehicles under the limitations of transportation capacity.

Researches of fleet routing and scheduling problems mainly consider the problem of how to transport resource to disaster points with the shortest time and minimum cost. Beside transport time and cost, there have more issues needed to be addressed in CCN deployment scheduling problem. First, the emergency levels of disaster areas are different. The profits of delivering materials to disaster areas to recover base stations are also different. Hence, the disaster area, which has higher emergency level, should have higher priority. Second, the profits are not constant but decreasing with time. Third, the deployment sequence has to follow the scheduling constraint. In order to solve these issues, a CCN deployment scheduling (CCN-DS) formulation is proposed [27]. And, a CCN-DS algorithm is used to find a heuristic deployment scheduling to approximately maximize the efficiency of disaster response operation.

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 Priority Based Bandwidth Allocation and Admission Control

The system capability of a CCN is mainly limited by the bandwidths of the external link from the CCN to the core network, the inter-base-station links, and the radio channels from the base stations to cell phones. The bandwidth demand from users in a disaster typically far exceeds capacity. Therefore, some priority-based admission control must be implemented, in addition to a precise allocation plan that rationally distributes available bandwidth to base stations and maximizes CCN efficiency. Similar to the previous two problems, bandwidth allocation challenges were modeled into combinatorial optimization problems and solved using heuristic algorithms [25].

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