A novel energy-efficient data aggregation protocol for cognitive radio based wireless multimedia networks

In recent days, wireless multimedia cognitive radio networks (WMCRN) become a hot research topic due to its wide range of delay intolerant and time-critical applications. However, the increasing requirement of multimedia applications by cognitive radio networks (CRN) poses several design issues like energy efficiency, interferences, computational speed and memory. Due to the battery operated sensor nodes in WMCRN, it is very difficult to upload all multimedia information to the user in remote areas. Therefore, it is highly needed to design an energy-efficient data aggregation technique to minimize the data traffic and lengthen the network lifetime. But the conventional data aggregation schemes are not adaptable to the requirements of WMCRN due to the handling of massive sized multimedia data. In this view, this paper presents a new energy efficient Link Selection with Data Aggregation (EELSDA) Protocol for WMCRN. The proposed EELSDA model makes use of data aggregation factor in the link selection process of the graph routing technique. The proposed EELSDA model increases the possibility of data fusion at the intermittent routing nodes and minimizes the amount of data transmission in the network. The proposed EELSDA model utilizes link quality, communication energy and transmission frequency to select the optimal set of links. Consequently, reliability links to parent nodes with maximum remaining energy will be chosen for ensuring the success ratio for data transmission and total energy balancing of the network. Moreover, the relation among the transmission frequencies of the child as well as parent nodes represents the significant packet delay for data fusion in the specific parent node. A series of simulation results are carried out to ensure the effective performance of the EELSDA protocol over the compared methods in a significant way. The maximum network lifetime has been attained by the EELSDA model than all other models under diverse number of nodes. For sample, under the presence of 350 nodes, the EELSDA approach has obtained maximum lifetime of 2240 while the SPEED, MMSPEED, RAP and SAP technologies have resulted in lower lifetime of 1400, 1690, 1790 and 2100 correspondingly.