Hakan Gultekin

The impact of one-time energy costs on network lifetime in wireless sensor networks

In this letter, we present a mixed binary linear programming framework to investigate the impact of one-time energy costs on the overall system lifetime in wireless sensor networks. We use public-key cryptography as our representative one-time initialization operation. We show that the effect of public-key cryptography on optimal routes selection depends on the ratio of electronics energy to amplifier energy. The simulation results also reveal that the impact of public key cryptography on the maximum achievable lifetime of a sensor network is not negligible and it does not steadily increase with the size of the network.

Robotic cell scheduling with operational flexibility

In this paper, we study the problem of two-machine, identical parts robotic cell scheduling with operational flexibility. We assume that every part to be processed has a number of operations to be completed in these two machines and both machines are capable of performing all of the operations. The decision to be made includes finding the optimal robot move cycle and the corresponding optimal allocation of operations to these two machines that jointly minimize the cycle time. We prove that with this definition of the problem 1-unit robot move cycles are no longer necessarily optimal and that according to the given parameters either one of the 1-unit robot move cycles or a 2-unit robot move cycle is optimal. The regions of optimality are presented.

Maximizing lifetime of event-unobservable wireless sensor networks

In wireless sensor networks (WSNs) contextual information such as the information regarding whether, when, and where the data is collected cannot be protected using only traditional measures (e.g., encryption). Contextual information can be protected against global eavesdroppers by periodic packet transmission combined with dummy traffic filtering at proxy nodes. In this paper, through a Linear Programming (LP) framework, we analyze lifetime limits of WSNs preserving event-unobservability with different proxy assignment methodologies. We show that to maximize the network lifetime data flow should pass through multiple proxies that are organized as a general directed graph rather than as a tree.

Scheduling in a three-machine robotic flexible manufacturing cell

In this study, we consider a flexible manufacturing cell (FMC) processing identical parts on which the loading and unloading of machines are made by a robot. The machines used in FMCs are predominantly CNC machines and these machines are flexible enough for performing several operations provided that the required tools are stored in their tool magazines. Traditional research in this area considers a flowshop type system. The current study relaxes this flowshop assumption which unnecessarily limits the number of alternatives. In traditional robotic cell scheduling literature, the processing time of each part on each machine is a known parameter. However, in this study the processing times of the parts on the machines are decision variables. Therefore, we investigated the productivity gain attained by the additional flexibility introduced by the FMCs. We propose new lower bounds for the 1-unit and 2-unit robot move cycles (for which we present a completely new procedure to derive the activity sequences of 2-unit cycles in a three-machine robotic cell) under the new problem domain for the flowshop type robot move cycles. We also propose a new robot move cycle which is a direct consequence of process and operational flexibility of CNC machines. We prove that this proposed cycle dominates all 2-unit robot move cycles and present the regions where the proposed cycle dominates all 1-unit cycles. We also present a worst case performance bound of using this proposed cycle.

Pure cycles in flexible robotic cells

In this study, an m-machine flexible robotic manufacturing cell consisting of CNC machines is considered. The flexibility of the machines leads to a new class of robot move cycles called the pure cycles. We first model the problem of determining the best pure cycle in an m-machine cell as a special travelling salesman problem in which the distance matrix consists of decision variables as well as parameters. We focus on two specific cycles among the huge class of pure cycles. We prove that, in most of the regions, either one of these two cycles is optimal. For the remaining regions we derive worst case performances of these cycles. We also prove that the set of pure cycles dominates the flowshop-type robot move cycles considered in the literature. As a design problem, we consider the number of machines in a cell as a decision variable. We determine the optimal number of machines that minimizes the cycle time for given cell parameters such as the processing times, robot travel times and the loading/unloading times of the machines.

Scheduling in robotic cells: process flexibility and cell layout

The focus of this study is the identical parts robotic cell scheduling problem with m machines under the assumption of process and operational flexibility. A direct consequence of this assumption is a new robot move cycle that has been overlooked in the existing literature. We prove that this new cycle dominates all classical robot move cycles considered in the literature for m = 2. We also prove that changing the layout from an in-line robotic cell to a robot-centered cell reduces the cycle time of the proposed cycle even further, whereas the cycle times of all other cycles remain the same. For the m-machine case, we find the regions where the proposed cycle dominates the classical robot move cycles, and for the remaining regions present its worst case performance with respect to classical robot move cycles. Considering the number of machines as a decision variable, we also find the optimal number of machines that minimizes the cycle time of the proposed cycle.

Cyclic scheduling of a 2-machine robotic cell with tooling constraints

In this study, we deal with the robotic cell scheduling problem with two machines and identical parts. In an ideal FMS, CNC machines are capable of performing all the required operations as long as the required tools are stored in their tool magazines. However, this assumption may be unrealistic at times since the tool magazines have limited capacity and in many practical instances the required number of tools exceeds this capacity. In this respect, our study assumes that some operations can only be processed on the first machine while some others can only be processed on the second machine due to tooling constraints. Remaining operations can be processed on either machine. The problem is to find the allocation of the remaining operations to the machines and the optimal robot move cycle that jointly minimize the cycle time. We prove that the optimal solution is either a 1-unit or a 2-unit robot move cycle and we present the regions of optimality. Finally, a sensitivity analysis on the results is conducted.

Bicriteria robotic operation allocation in a flexible manufacturing cell

Consider a manufacturing cell of two identical CNC machines and a material handling robot. Identical parts requesting the completion of a number of operations are to be produced in a cyclic scheduling environment through a flow shop type setting. The existing studies in the literature overlook the flexibility of the CNC machines by assuming that both the allocation of the operations to the machines as well as their respective processing times are fixed. Consequently, the provided results may be either suboptimal or valid under unnecessarily limiting assumptions for a flexible manufacturing cell. The allocations of the operations to the two machines and the processing time of an operation on a machine can be changed by altering the machining conditions of that machine such as the speed and the feed rate in a CNC turning machine. Such flexibilities constitute the point of origin of the current study. The allocation of the operations to the machines and the machining conditions of the machines affect the processing times which, in turn, affect the cycle time. On the other hand, the machining conditions also affect the manufacturing cost. This study is the first to consider a bicriteria model which determines the allocation of the operations to the machines, the processing times of the operations on the machines, and the robot move sequence that jointly minimize the cycle time and the total manufacturing cost. We provide algorithms for the two 1-unit cycles and test their efficiency in terms of the solution quality and the computation time by a wide range of experiments on varying design parameters.

Two-machine flowshop scheduling with flexible operations and controllable processing times

We consider a two-machine flowshop scheduling problem with identical jobs. Each of these jobs has three operations, where the first operation must be performed on the first machine, the second operation must be performed on the second machine, and the third operation (named as flexible operation) can be performed on either machine but cannot be preempted. Highly flexible CNC machines are capable of performing different operations. Furthermore, the processing times on these machines can be changed easily in albeit of higher manufacturing cost by adjusting the machining parameters like the speed and/or feed rate of the machine. The overall problem is to determine the assignment of the flexible operations to the machines and processing times for each operation to minimize the total manufacturing cost and makespan simultaneously. For such a bicriteria problem, there is no unique optimum but a set of nondominated solutions. Using @e-constraint approach, the problem could be transformed to be minimizing total manufacturing cost for a given upper limit on the makespan. The resulting single criterion problem can be reformulated as a mixed integer nonlinear problem with a set of linear constraints. We use this formulation to optimally solve small instances of the problem while a heuristic procedure is constructed to solve larger instances in a reasonable time.

Maximizing Wireless Sensor Network lifetime by communication/computation energy optimization of non-repudiation security service

In a typical Wireless Sensor Network (WSN) application, the basic communication service is the transportation of the data collected from sensors to the base station. For prolonging the network lifetime, energy efficiency should be one of the primary attributes of such a service. The amount of data transmitted by a node usually depends on how much local processing is performed. As an example, in visual sensor networks the amount of image processing on the nodes affects the amount of data transmitted to the base station (i.e., the higher the computation, the lower the communication and vice versa). Hence in order to improve energy efficiency and prolong the network lifetime this communication/computation energy trade-off must be analyzed. This analysis may be performed at the network-level (i.e., all nodes in the network use the same strategy) or at a node level (i.e., sensor nodes do not necessarily have identical strategies). The latter is more fine-grained allowing different nodes to implement different solutions. To guide designers in effectively using these trade-offs to prolong network lifetime, we develop a novel Mixed Integer Programming (MIP) framework. We show that the optimal node level strategy can extend network lifetime more than 20% as compared to a network-level optimal strategy. We also develop a computationally efficient heuristic to overcome the very high computational requirements of the proposed MIP model.