# A New Intra-Cluster Scheduling Scheme for Real-Time Flows in Wireless Sensor Networks
## 1 Introduction  
WirelessHART standards for sensor-actuator networks have attracted interest for real-time communication [1]. These protocols use a centralized approach for the transmission schedule and avoid concurrent transmissions with the same channel. The approach uses a different priority scheme and achieves the real-time communication through time division multiple access (TDMA) scheduling. This standard increases the amount of delay and limits scalability. In the quality of service-aware cluster-based data sending schemes [2], each node transmits the sensing data to its cluster head, which in turn, aggregates that data and sends the results to the base station. The whole scheme consists of intra-cluster data reporting and inter-cluster control methods. For intra-cluster data, only a few member nodes were selected as reporting nodes to meet the required throughput and save energy for other rounds. At the same time, for inter-cluster controls, delay-bound data were routed using a minimum number of hops consisting of a combination of cluster heads and member nodes. The real-time query scheduling algorithm [3] assumes a pre-given routing tree for different scheduling strategies by considering the trade-offs between prioritization and throughput. The problem with TDMA scheduling for flat wireless sensor networks (WSNs) is that they are not scalable to the large networks, and have less slot reuse due to global view of the network [4] or large message exchanges. Hence, they lack in performance metrics like delay which is not efficient for real-time communication. Therefore, TDMA scheduling under cluster architecture is proposed in WSNs [5; 6; 7; 8]. Adaptive distributed randomized [10] is a cluster-based TDMA scheme for wireless sensor networks. The slots are assigned to the node based on the one-hop and two-hop neighbor's information. The cluster heads are allocated more slots, and hence improve channel utilization and throughput. However, for energy balance, the cluster head is alternated by other cluster members, which increases overhead due to the reassignment of slots. The cluster-tree model [10] based on a single-channel and time division cluster schedule--proposes a receiver-oriented scheduling algorithm that offers bounded latency for data gathering applications and reduces the interference among clusters. In [11], real-time query services were scheduled where data are routed from many-to-one communication by avoiding the interference by using the interference graph. Cluster-based real-time communication scheme [12] represented interference by using graph theory, while graph coloring is used to avoid the collision. In [13], real-time packets are scheduled under the WirelessHART model. This model contains multiple channels, avoiding the interference by allowing one transmission in each channel in a time slot. In [14], an adaptive clustering scheme was proposed for event-driven applications. In this scheme, the clusters were adapted according to the change in event sensing so that cluster-based structure proved performance in real-time WSNs. However, information accuracy was reduced by combining the packets. In [15], the real-time capacity for wireless network by assuming ideal TDMA was proposed to deliver the data by their deadlines. They provided relevant contributions to the theoretical understanding of real-time capacity of multi-hop WSNs. However, the applicability of results to a real WSN may not be applied in practice due to implementation of a medium arbitration with zero overhead. Real-time WSN are becoming an ever more important emerging communication infrastructure for real-time applications. Examples of such applications are habitat monitoring, forest monitoring, disaster management, seismic monitoring and smart cities [16]. These types of systems are time-critical and performance-sensitive. In time-critical event detection applications, detecting events after the predefined time frame may have catastrophic consequences.