Economic Trade-offs in Network Architecture Design

1. Economic Trade-offs in Network Architecture Design Joe Bater 4C 22nd June 2005 Collaborative work with: Ken Brown 4C Linda Doyle Trinity College Tim Forde Trinity College Frank Mullany Bell Labs Ireland

2. Evolution of Cellular Network Technologies Circuit switching voice and low speed data services High-speed circuit switching data service on GSM Circuit switching voice service (GSM) and packet switching data service GSM/EDGE Radio Access Network providing IP multimedia service through IMS (Release 5) Enhanced data rates on GPRS 2G 2.5G 3G GSM HSCSD GPRS EDGE (EGPRS) GERAN UMTS UTRAN UMTS Radio Access Network Economic Trade-offs in Network Architecture Design

3. Implications for Backhaul Network Design • The level of user demand and the data rates supplied is dramatically growing, with typical maximum user rates: • of 384kbps in 3G (Release 4 of UMTS), • to 2.4Mbps in CDMA2000-EVDO, • to rates in excess of 10Mbps in HSDPA (Release 5 of UMTS). • This is further complemented by short-range 802.11 WLAN wireless connectivity at rates of up to 54Mbps. • This requires an equivalent expansion of the existing networks which transfer data from the access network back to and from the core network (backhaul). Economic Trade-offs in Network Architecture Design

4. Backhaul Network Architecture Design Choices • Given a plan for a cellular network, and a worst-case estimate on the traffic demand for each site in the access network – • What is the most cost effective network design to ensure that all traffic gets back to the core network (backhaul) whilst meeting acceptable delay constraints? • What elements of the network are critical in terms of installation and operating cost? • We are extending the state of the art by adding the inclusion of wireless WiMAX links – • Thus our solutions must be based on expected traffic demand, cheapest link media, line delays and scheduling delays • The question is then:“what is the sweet-spot between wired and wireless backhaul?” Economic Trade-offs in Network Architecture Design

5. Network Design Features • External constraints on the network – • Base station location: x, y, z co-ordinates, and location type • Traffic demands on each base station • Max allowable delays • Locations of possible aggregator nodes for grooming traffic • Locations of gateway nodes to core network • Network Capabilities – • To calculate the throughput/delay on WiMAX link we use link budgets and the SUI Category B shadowing model • Economic Factors – • Costs of trenching and cabling • Costs of node types and equipment subsystems: line cards, aggregation units, WiMAX baseband units and radios Economic Trade-offs in Network Architecture Design

6. Scenario One : Trinity College Dublin (1) • 53 UMTS nodes B/WiFi hotspots, 2 aggregator nodes, and 1 core node have been placed • we have wireless link capacities (including some cases in which links are not possible) • delays are constrained by a maximum hop count setting • costs for wireless equipment and wired links are assumed • all links are Euclidean (straight-line) distance between nodes Economic Trade-offs in Network Architecture Design

7. Scenario One : Trinity College Dublin(2) Economic Trade-offs in Network Architecture Design

8. Scenario Two : Randomised Problems (1) • access nodes, aggregator nodes, and core nodes are placed randomly on a flat plane • between 10 and 200 access nodes • between 2 and 10 aggregator nodes • up to 3 core network node • 802.16 link capacities generated for each instance – shadowing is stochastic • costs are assumed but configurable (several cost functions available) • delays are constrained by a maximum hop count setting • all links are Euclidean distance between nodes – noise factor for non-Euclidean trenching can be added Economic Trade-offs in Network Architecture Design

9. Scenario Two : Randomised Problems (2) Economic Trade-offs in Network Architecture Design

10. Scenario Three(?) • We are looking for more scenarios. It could be yours! • Of particular interest would be heavy urban environments in which trenching costs are disproportionately large, and space in radio units limited… Economic Trade-offs in Network Architecture Design

11. Network Design Algorithms • Many of the problems pertaining to backhaul design are relatively simple, and can be solved in polynomial time using modified Dijkstra or Ford-Fulkerson algorithms. • However, as soon as optimising for cost becomes part of the problem, it generally shifts to NP-hard complexity. Additionally we are allowing the link media to be chosen, and moving to adding constraints on the types and amounts of equipment. • As a consequence most modern solution approaches tend to be heuristic. Local search algorithms offer good solutions quickly, rather than strictly ensuring the best possible solution which may take too long to compute. Economic Trade-offs in Network Architecture Design

12. Plateau Local optimum Global optimum Local Search and Local Optima • Suppose we have a (typically very large) space of candidate solutions and a neighbourhood relation on this space. Local searches start from an initial candidate solution and then make moves from one candidate solution to another candidate solution from its direct neighbourhood. • A local optimum is a solution optimal within a neighbouring set of solutions. This is in contrast to a global optimum, which is the optimal solution of the whole solution space. Economic Trade-offs in Network Architecture Design

13. Iterated Local Search • Iterated Local Search (ILS) is a simple, robust and modular meta-heuristic search technique based on repeated (iterated) use of a local search algorithm. • After each run of the local search (i.e. when the current solution candidate is a local optima) the candidate solution state is perturbed somehow. • The basic form of ILS is thus: • GenerateInitialSolution • LocalSearch • while not done • Perturb • LocalSearch • AcceptanceCriteria • end while Economic Trade-offs in Network Architecture Design

14. Optimization Tool Output Example Typical result of 100 iterations of ILS, average run-time taking approx. 4 minutes Economic Trade-offs in Network Architecture Design

15. Summary • We have examined the performance of several state-of-art meta-heuristic search types, including Simulated Annealing and Tabu Search • Additionally we are planning to tackle the problem with CP and ILP techniques • ILS is currently the consistently best performing search method, but even then runs of ILS can be inconsistent, • We have begun to use an analysis of the search landscape to design perturbation schemes • We have seen that the problems display sensitivity to changes in the equipment costs • A scientific sensitivity analysis on a range of costs is planned for the near future Economic Trade-offs in Network Architecture Design