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Performance improvement for mobile ad hoc cognitive packets network
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn this thesis, focusing on the quality of service (QoS) improvement using per-packet power control
algorithm in Ad Hoc Cognitive Packet Networks (AHCPN). A power control mechanism creates as a
network-assisted function of ad hoc cognitive packet-based routing and aims at reducing both energy
consumption in nodes and QoS requirements. The suggested models facilitate transmission power
adjustments while also taking into account the effects on network performance.
The thesis concentrate on three main contributions. Firstly, a power control algorithm, namely the
adaptive Distributed Power management algorithm (DISPOW) was adopted. Performance of DISPOW
was compared to existing mechanisms and the results showed 27, 13, 9, and 40 percent improvements
in terms of Delay, Throughput, Packet Loss, and Energy Consumption respectively.
Secondly, the DISPOW algorithm was enhanced, namely a Link Expiration Time Aware Distributed
Power management algorithm (LETPOW). This approach periodically checks connectivity, transmission
power, interference level, routing overhead and Node Mobility in AHCPN. The results show
that LETPOW algorithm improves the performance of system. Results show further improvement
from DISPOW by 30,25,30,42 percent in terms of delay, packet loss ratio , path lengths and energy
consumption respectively.
Finally,Hybrid Power Control Algorithm (HLPCA) has presented is a combination of Link Expiration
Time Aware Distributed Power management algorithm (LETPOW) and Load Power Control
Algorithm (LOADPOW); deal with cross-layer power control applied for transmitting information
across the various intermediate layers. LOADPOW emphasis on the concept of transmission Power,
Received Signal Strength Indication (RSSI), and the suitable distance between the receiver and the
sender. The proposed algorithm outperforms DISPOW and LETPOW by 31,15,35,34,44 percent in
terms of Delay, Throughput, Packet Loss,path length and Energy Consumption respectively. From
this work, it can be concluded that optimized power control algorithm applied to Ad-hoc cognitive
packet network results in significant improvement in terms of energy consumption and QoS
Cross-layer Balanced and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks
For improving the efficiency and the reliability of the opportunistic routing
algorithm, in this paper, we propose the cross-layer and reliable opportunistic
routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the
improved efficiency fuzzy logic and humoral regulation inspired topology
control into the opportunistic routing algorithm. In CBRT, the inputs of the
fuzzy logic system are the relative variance (rv) of the metrics rather than
the values of the metrics, which reduces the number of fuzzy rules
dramatically. Moreover, the number of fuzzy rules does not increase when the
number of inputs increases. For reducing the control cost, in CBRT, the node
degree in the candidate relays set is a range rather than a constant number.
The nodes are divided into different categories based on their node degree in
the candidate relays set. The nodes adjust their transmission range based on
which categories that they belong to. Additionally, for investigating the
effection of the node mobility on routing performance, we propose a link
lifetime prediction algorithm which takes both the moving speed and moving
direction into account. In CBRT, the source node determines the relaying
priorities of the relaying nodes based on their utilities. The relaying node
which the utility is large will have high priority to relay the data packet. By
these innovations, the network performance in CBRT is much better than that in
ExOR, however, the computation complexity is not increased in CBRT.Comment: 14 pages, 17 figures, 31 formulas, IEEE Sensors Journal, 201
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