## 3 Related Work  
In communication systems and wireless sensor network systems, many studies have been proposed to solve scheduling problems [20; 21; 22; 23; 24; 25].  
In a FieldBus environment, scheduling problems of dynamic or static collecting information flow are to be found in [20; 21]. Algorithms capable of solving this problem have to be able to calculate the transmission sequence for all groups. The solution is firstly to decide the primary cycle among multiple cycles. The primary cycle is the shortest period. Then, if there are two polling tasks of different groups at the same time, the group whose polling cycle is \(T_{i}\) always has higher priority than group whose polling cycle is \(T_{j}\), where \(T_{i}\leq T_{j}\). In the papers, authors assume that deadline coincides with the polling cycle, and scheduling problem is to ensure that at least one transmission for each group will occur at least once in the cycle. They do not address features of wireless communication.  
In [22], the authors propose TDMA link scheduling algorithms for the purpose of maximizing network throughput. In [23], an end-to-end real-time transmission scheduling over the wirelessHART networks is proposed. Both [22; 23] are focus on making conflict-free link level schedules. According  
Figure 3: Position of our data traffic control scheme in function layers.  
to these schedules, end devices can autonomously transmit periodical sensor data to a center node within a deadline according to the schedule but this communication is not polling-based.  
In [24], the authors show through analysis and experiments that conflict-free query scheduling has an inherent tradeoff between network throughput and latency. They propose real-time scheduling algorithms for prioritized conflict-free transmission scheduling in order to aim to balance network throughput and latency.  
In [25], a new priority-based parallel schedule polling MAC protocol in WSNs combines polling orders with access policies to realize the priority-based scheme and reduce the overhead time through parallel schedule. Sensor nodes can be classified in different clusters and this MAC protocol coordinates all clusters and gives a chance to send data in order. To do this, the node to which a central node wants to transmit a priority packet is given the transmission chance first, and other nodes remain in a sleeping status to save energy.  
As will be descried in Section 6, we adopt a GA (genetic algorithm) as a heuristic to derive an optimal schedule [26]. GA is one of probabilistic search algorithms and optimization techniques based on the mechanisms of natural selection and evolution. It has been applied to optimization of complex network management problems such as network load balancing management [27] and routing [28]. Although other heuristic algorithms such as simulated annealing, PSO (particle swarm optimization), or even machine learning can also be adopted, we consider a GA-based algorithm in this paper, which could achieve a reasonable and feasible schedule with practically short computation time on an off-the-shelf computer.  
Our work is different from related work in the following aspects. As shown in Table 1, other works focus on how to schedule transmitting queries without conflicts in order to minimize network latency, optimize network throughput, or save energy. However, none of them focuses on the problem that unbalanced network bandwidth between uplink and downlink causes unexpected big latency of unpredictable on-demand communication or decrease of success probability for periodic data collection. We firstly propose a polling-based data traffic control scheme which is available to any IWSN protocols that assign unequal bandwidth to upstream and downstream communication. In addition, we show a scheduling using a network traffic uniformity metric for IWSNs to realize both scheduled periodic data collection at high success ratio and unpredictable on-demand communications with short latency.