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Cutting-Edge Wireless Network Management Research Topics

Explore innovative topics such as Radio Resource Management Scheme for WLAN, Load Balancing Algorithms, Data Replication Strategies, and more. Delve into analytical modeling, empirical simulations, and the challenges of network resource allocation. Understand the impact of replication and erasure codes on data availability and latency. Discover optimal strategies for object replication and positioning, considering device load, network distance, and object types. Quantitatively compare replication and erasure-resilient systems for multimedia and text objects.

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Cutting-Edge Wireless Network Management Research Topics

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  1. Proposed Research Topics Spring 2003 Abed E. Lawabni & Prof. Ahmed H. Tewfik { lawabni, tewfik }@ ece.umn.edu

  2. Road Map • Radio Resource Management Scheme for WLAN. • Dynamic Frequency Allocation. • Wireless Link Aggregation (Routing-Flow Optimization). • Load Balancing Algorithms. • Data Replication Vs. Erasure codes.

  3. Radio Resource Management Scheme for WLANEfficient and Robust Data Paths • Providing an efficient data path between the client and the remote storage device to achieve: • Low latency. • High throughput. • Supporting different applications.

  4. Radio Resource Management Scheme for WLAN Switching Hub Gigabit Backbone IP Network within a Region OSD IEEE 802.11 AP IEEE 802.11 AP OSD OSD OSD Web Object Multimedia Object Text Object Where it should be associated ? What type of traffic is going to be requested?

  5. Radio Resource Management Scheme for WLAN(continue) • Analytical Modeling. • { traffic type, distance effect, PER, # of competing stations, etc.} • An Empirical (Measurement-based) Simulation.

  6. Data Replication • When a decision to replicate is made , where is the replicated object located? • Main Challengeis that future demand is anunknown. • Formulating the object replication & positioning problem as a Stochastic network resource allocation problem. • Different terms in the cost Function: • Cross-correlation between observed demand for the objects and that of other objects with a known demand load & location history. • Delay in accessing the object based on multi-queue models. • Allowing various priorities to be assigned to objects.

  7. Data Replication • Selecting the best replica from a set of replicas. • Network distance (hop counts, round-trip time, bandwidth) • Device load in delivering the best object to the client. • Different object types may also require different performance metrics: Multimedia objects vs. text objects. • Erasure-resilient system Vs. Replication system. Quantitative Comparison: • Time to failure. • Storage & Bandwidth requirements. • Replication strategies for compound objects such as MPEG-21 objects.

  8. Thanks • Prof. Ahmed H. Tewfik tewfik@ece.umn.edu EE/CSci Building,Room # 6–177 • Abed E. Lawabni lawabni@ece.umn.edu EE/CSci Building, Room # 6–120

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