دانلود رایگان مقاله تعامل تعاونی در میان موارد RPL در شبکه های حسگر بی سیم

Abstract

Advanced Wireless Sensor Networks (WSNs) applications may need to develop multiple tasks that involve sensing, processing and gathering data from different sensing units. This heterogeneous data may have multiple and sometimes opposite sets of requirements. In these scenarios, different networking strategies must be combined, and therefore traditional single-tree routing approaches are not efficient. On the contrary, the well-known RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) protocol virtually splits the network into multiple RPL Instances, that transport each kind of data according to its particular objective function. However, this protocol does not define any mechanism to decide the nodes that must belong to each instance, and this decision has a strong impact in the network energy consumption and performance. With this in mind, in this paper we introduce C-RPL (Cooperative-RPL). This creates multiple instances following a cooperative strategy among nodes with different sensing tasks. As a result, the energy consumption, the complexity and the cost of the nodes is reduced compared to RPL, since they are active less time, perform fewer tasks and are equipped with less sensing hardware. In this paper we also propose a novel fairness analysis for networks with multiple instances, showing that C-RPL achieves a better tradeoff, in terms of performance and energy consumption, than RPL with non-cooperative instances.

7. Conclusion

Advanced WSN applications may need to sense, process and transmit data coming from different sensing units. As a result, different and maybe opposite sets of requirements must be satis- fied in the same network. The well-known RPL protocol addresses this problem creating independent RPL Instances for traffics with different objective functions. However, it does not define the nodes that must belong to each instance, and this decision has a strong impact in the network energy consumption and performance. Therefore, in this paper we introduce C-RPL (Cooperative-RPL), that creates energy efficient instances, adapted to the particular QoS requirements of each traffic. These instances are constructed following a cooperative strategy among nodes with different sensing tasks. Since nodes would never agree to cooperate, as we have shown in this paper, C-RPL coordinates them to create coalitions that improve the tradeoff between their own performance metric and energy consumption, using the cooperation parameter α. The simulation results show that C-RPL efficiently creates the C-RPL Instances according to their individual objective functions and the particular network conditions. In particular, we have observed that C-RPL tends to create large instances when the node density is low. Otherwise, it constructs smaller instances to reduce the energy consumption of the network and avoid congestion problems. Besides, we have proposed a fairness analysis for networks with multiple instances that measures the distribution of the network resources when multiple objective functions coexist in the network. The results show that C-RPL obtains a more balanced fairness in terms of performance and energy consumption than RPL approaches with non-cooperative instances.