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Topology Design of Structured Campus Networks by Habib Youssef Sadiq M. Sait Salman A. Khan Department of Computer Engineering King Fahd University of Petroleum and Minerals. Outline. Introduction & Problem Statement Proposed Algorithm Simulated Evolution
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Topology Design of Structured Campus Networks by Habib Youssef Sadiq M. Sait Salman A. Khan Department of Computer Engineering King Fahd University of Petroleum and Minerals
Outline • Introduction & Problem Statement • Proposed Algorithm • Simulated Evolution • Fuzzy Evaluation Scheme • Selection • Fuzzy Allocation Scheme • Experiments and Results • Conclusion
Introduction • Important objectives of good topology • Monetary Cost • Average network delay • Number of hops between any source-destination pair • Conflicting nature of the objectives
Constraints • Limitation of capacity on links • Limitation of ports on networking devices • Another possible constraint is that the designer might like to enforce certain hierarchies on network devices. • Topology is a tree
Purpose • Given the optimization parameters and constraints, we have to design a Spanning Tree Topology to satisfy all the constraints and optimize desired objectives.
Objectives of Good Topology Design • Monetary Cost • Reduction in monetary cost s = total cable length ccable = cost per unit of cable used cnd= cost of network devices
Objectives of Good Topology Design • Average Network Delay per packet • Reduction in the average network delay due to links. = total traffic in the network, ij = traffic between clusters i and j i j = delay per bit due to network device between cluster i and j
Objectives of Good Topology Design • Maximum hops between any source-destination pair. • This includes the networking devices due to which processing delays are encountered.
Simulated Evolution B = Bias value; ei = Individual link in Ci = Current cost of ith link in ; = complete solution Oi = Lower bound on cost of ith link gi = Goodness of ith link in S = Queue to store the selected links; INITIALIZATION Repeat EVALUATION : ForEach ei DO gi = Oi / Ci SELECTION : ForEach ei DO IF Random > Min (gi + B, 1) THEN begin S = S U ei ; Remove ei from end Sort element of S ALLOCATION : ForEach ei S DO ALLOCATE(ei ,) Until Stopping condition is satisfied. Return Best Solution
Evaluation • Goodness = Oi / Ci • A link is the individual to be evaluated, based on • Its cost. • Its depth in the current topology with respect to the root. • Goodness of link with respect to cost • Link with minimum cost (LCostMin). • Link with maximum cost (LCostMax).
Evaluation • Done using fuzzy logic. • Thus, we make a membership function which consists of the minimum, maximum, and the current cost and compare “goodness of link with respect to cost” using this function.
1.0 0.5 LCost LCostMax LCostMin LCostMax 1 Evaluation Membership of a kink in fuzzy subset “Link Cost”
Evaluation • Goodness of link with respect to depth • Minimum depth of link =1 (LDepthMin) • Maximum depth of link = (1.5) *Max. depth of any link in the first generation OR Maximum of 7 (LDepthMax)
Evaluation 1.0 0.5 LDepth LDepthMin LDepthMax Membership of a link in fuzzy subset “ Link Depth”
Evaluation • The two fuzzy goodness functions are combined using fuzzy rule. • The fuzzy rule used is: If the link has near optimum costAND near optimum depth THEN the link has high goodness. • Using OWA - andlike:
Selection • Based on the goodness found in the evaluation phase, link(s) is (are) selected to be removed from the topology. • Done using • Variable bias Bk = 1 - Gk-1 where Gk-1 is the average goodness of links in K-1st iteration
Allocation • Moves are made and the gain in cost of the overall topology is calculated based on • Monetary cost of the topology • Average network delay per packet • Maximum number of hops between any source-destination pair.
Allocation • For Monetary Cost, the minimum and maximum bounds are calculated as follows: • Minimum : from Esau-Williams algorithm with all the constraints fully relaxed. (TCostMin) • Maximum : we find it from the very first generation. (TCostMax)
Allocation 1.0 0.5 TCost TCostMax TCostMin TCostMax 1 Membership function of a tree in fuzzy subset of low cost trees
Allocation • For Average Network Delay, the minimum and maximum bounds are calculated as follows: • Minimum : delay when all the nodes are connected directly to the center (TDelayMin). • Maximum : initial solution (TDelayMax).
Allocation 1.0 0.5 TDelay TDelayMax TDelayMin TDelayMax 1 Membership function of a tree in fuzzy subset of low average delay tree
Allocation • For Maximum number of hops, the minimum and maximum bounds are calculated as follows: • minimum : 1 hop (THopsMin). • maximum : initial solution (THopsMax).
Allocation 1.0 0.5 THops ThopsMin THopsMax Membership function of a tree in fuzzy subset of low maximum number of hops between any s-d pair
Allocation • The three fuzzy tree measures are combined using the following fuzzy rule: If a solution has low monetarycostAND low average network delay AND low maximum hopsAND it is a good topology. • Using OWA - andlike:
Allocation • What is our move ? • For each selected link, maximum 10 moves are tried (valid or invalid) • Five greedy • Five random • Pick the move which gives the maximum gain among all the moves.
Tabu Search • Diversifies the search by imposing restrictions on the search process, preventing it from moving in certain directions.
Assumptions • The number of segments is known a priori and nodes have already been assigned to segments. • The location of a segment (or of a local site) is represented by its (x,y) coordinates with respect to some reference point. • A node is either 10/100baseT Ethernet or Token Ring Type. • A local site is made of 10/100BaseT Ethernet segments or all Token Ring segments.
Assumptions • The backbone is assumed to be running on Fast Ethernet using fiber optic cable. • Within a local site, only Category 5 cable is used, while between two local sites, only fiber optic cable is used . • Class C networks are assumed. Therefore, we limit the number of nodes per cluster to at most 254. • Hubs, switches, routers, and other networking devices cannot be placed in any location. There are designated location to do so.