## 2 Related Work  
An aspect not specified in the IEEE 802.15.4 standard is the construction of a TSCH schedule. Therefore, this task has attracted great attention from the research community. In centralized schemes, a central entity collects the entire network information and then calculates the link schedules. TASA [7] is a centralized approach where the schedule is built by a single node. This scheduling builds time/frequency patterns based on the network topology graph and the traffic load at each node, while reducing latency and radio duty-cycle at the same time. The CLS [8] algorithm constructs efficient multi-hop schedules using a minimal number of centralized control messages, because it allocates and deallocates slots without rescheduling the entire schedule every time. CLS focuses on the reduction of idle listening, while addressing bandwidth requirements of the network. In [9], the authors proposed another centralized raw data convergecast scheduling, called Multichannel Optimized Delay time Slot Assignment (MODESA), which takes into account the availability of multiple channels to reduce the TDMA cycle length while ensuring a fair medium access. It sorts the nodes according to their priorities, where the highest priority corresponds to the highest number of remaining packets in one node's buffer. Although these approaches present a theoretical scheduling which seems efficient, actually, the disadvantage of centralized scheduling lies in the change of the topology. In this case, the update of the network information is done more slowly by the root, which becomes overloaded. This is why this type of centralized approach is recommended when the topology does not change much and therefore the environment is static. Then comes the distributed approach, which attempts to allocate cells through a procedure for establishing connections between neighbors. The distributed scheduling is more flexible when faced with sudden network changes than the centralized schemes, which collect information from the central entity and determine the schedule. DeTAS [10], one of them, is a distributed version of TASA that targets networks with several sink nodes. This distributed scheduling is a traffic-aware algorithm that builds the schedule based on the traffic generated by each source node where the network is modeled as multiple routing graphs, each rooted at a different sink. Wave, another distributed scheduling algorithm that schedules nodes in successive waves, is proposed in [11]. In each wave, each node having a packet to transmit is assigned a time slot and a channel. The sink node sends a message to its children to trigger the computation of the first wave. The particularity of this algorithm is that it minimizes the slotframe size required for the convergecast. Each slotframe is divided with a unit called the wave and generates waves repeatedly to form a schedule for all nodes in the network to transmit packets generated at regular intervals to the sink. In [12], DeAMON, which is decentralized adaptive multi-hop scheduling protocol for 6 TiSCH wireless networks, is introduced. This distributed scheduling for industrial monitoring and control applications offers solutions for upward traffic only and does not consider downward traffic. DIVA, a distributed divergecast scheduling algorithm, is presented in [13]. It is a completely distributed scheduling algorithm for divergecast traffic where nodes depart traffic to all neighbor nodes, as opposed to convergecast where leave nodes concentrate traffic towards the root node. Connections to neighbor nodes are established according to random opportunities independent of the network traffic rate at each node. Fundamentally, the distributed approach has weaknesses such as the need to negotiate between neighbors, which can lead to scheduling delay due to additional messaging. In autonomous scheduling, each node in the network determines the communication scheduling as the distributed approach.