A Performance Analysis Framework for WiFi/WiMAX Heterogeneous Metropolitan Networks Based on Cross-Layer Design

Martha Hernández Ochoa, Mario Siller, John Woods, Hector Alejandro Duran-Limon
2014 International Journal of Distributed Sensor Networks  
The communication between network nodes within different protocol domains is often regarded simply as a black box with unknown configuration conditions in the path. We address network heterogeneity using a white box approach and focus on its interconnection processes. To achieve this purpose, a Performance Analysis Framework (PAF) is proposed which is composed of the formalization of the latter using process algebra (PA) and the corresponding teletraffic performance models. In this
more » ... we target the IEEE 802.16 and IEEE 802.11 protocols. For the teletraffic models, we extend previous models for such scenario with the inclusion of the following protocol operational parameters (metrics): bit error rate (BER), packet error ratio (PER), and packet length (pl). From the framework teletraffic models, the optimal packet length (OPL), end to end throughput, delay, and packet loss are obtained. The PAF outperforms previous modeling solutions in terms of delay and throughput relative to NS3 simulation results. (1) Identify the network heterogeneity. This includes all the involved communication protocols across the available communication paths and domains. Use an end to end communication perspective. (2) Define the metrics to models. (3) Survey available teletraffic models for the identified communication protocols from each domain. (4) Extend and adapt the previous models according to the network design and corresponding performance metrics for each communication protocol or network domain. Use the CLD approach. (5) Identify the gateway nodes and the corresponding interconnection tasks defined in the protocol specification and network design. Base this identification process on the roles established on Section 4.1 (6) Derive the interconnection teletraffic models for the gateway nodes. (7) Based on the processes defined in Section 4.1, integrate all the involved teletraffic models across the communication paths under an end to end perspective. (8) Validate the end to end performance models using test bed implementations or network simulation. Improve teletraffic models if necessary. Box 1: White box approach. used by specific business processing engines, (4) the M2M area network, which enables connectivity between M2M components and M2M gateways, and (5) the M2M communication network (network domain) that provides connection between M2M gateway(s) and M2M application(s). Also, the M2M communication requires operational stability and sustainability [5] . The 802.16 protocol supports M2M applications in the 802.16p version [5] . This protocol enables a range of M2M applications in which the communication device requires wide-area wireless coverage in licensed bands and is automated, rather than human initiated or human-controlled. This is for purposes such as observation and control. The requirements that 802.16 is intended to address include low power consumption, a large number of devices, shortburst transmissions, and device tampering, detection, and reporting. The 802.16 protocol acts as an aggregation point for 802.16 M2M devices and supports peer to peer (P2P) connectivity between these devices [5, 8] . The 802.11 protocol in the version of IEEE802.11ah standard has been found as an optimal candidate for M2M communication in wireless communication systems. This protocol considers sensing applications and will address required functions such as low power consumption, large number of devices, long-range and short-burst data transmissions [9] . The 802.16 and 802.11 protocols can be part of an M2M network where M2M devices (communication enabled) form an M2M area network. This M2M area network is based on the IEEE802.11 protocol, whilst the access network that connects the M2M gateway (nodes with two interfaces: 802.11 and 802.16) to the M2M core (e.g., the 3rd Generation Partnership
doi:10.1155/2014/750971 fatcat:qxhhsccpajg27prz6y3z52hife