Venu  Madhav Kuthadi, Tshilidzi  Marwala, 
    Energy Efficient EMO Algorithm Based Scheduling Technique in
Wireless Sensor Networks,
    Asian Journal of Information Technology,
    Volume 16,Issue 11,
    2017,
    Pages 816-824,
    ISSN 1682-3915,
    ajit.2017.816.824,
    (https://makhillpublications.co/view-article.php?doi=ajit.2017.816.824)
    Abstract: In Wireless Sensor Networks (WSNs), the major problem in multiple sinks is efficient data collection
and scheduling which can be overcome by aggregated tree construction and TDMA based scheduling
technique. Earlier, the techniques used for aggregated tree construction process takes more iteration to
complete entire process which maximizes the scheduling delay. Therefore, there is need of an efficient
aggregated tree construction which reduces the wastage of iteration time. In this study, we propose energy
Efficient Multi-swarm fruit fly Optimization (EMO) algorithm for scheduling. In our EMO, the multi-swarm fruit
fly optimization technique is applied in Pocket Driven Trajectories (PDT) to minimize the delay and save energy.
Then Breadth First Search (BFS) algorithm is used for time slot scheduling process. The proposed EMO
algorithm reduces the iteration time to maximize the aggregated tree construction speed. The simulations show
that the proposed EMO algorithm significantly reduces the data collection delay and energy consumption.
    Keywords: Time Division Multiple Access (TDMA);Pocket Driven Trajectories (PDT);Breadth First Search (BFS);aggregated tree;scheduling;data collection