Optimal Resource Allocation for Markovian Queueing Networks: The Complete Information Case

The problem of finding the optimal routing and flow control of a single-class Markovian network under a suitable optimization criterion is analyzed. It is proven that, if complete information about the state of the network is made available to the network controller, the optimal state dependent routing is essentially deterministic, and the optimal flow control is of a generalized window type. An iterative linear programming algorithm is given for the derivation of the optimal routing and flow control policy

Load Balancing Algorithms for Jacksonian Networks with Acknowledgement Delays

Load balancing algorithms for Jacksonian networks are derived. The state of the network is represented by the total number of packets for which the source has not yet received an acknowledgement, The networks studied are subject to the state independent routing and, state dependent and state independent flow control. The objective is to maximize the throughput of the network so that the end-to-end expected packet time delay does not exceed an upper bound. The optimal flow control is shown to be a window type, while the routing policy balances the traffic inside the network. Several load balancing algorithms are evaluated

Asynchronous Algorithms for Optimal Flow Control of BCMP Networks

The decentralized flow control problem for an open multiclass BCMP network is studied. The power based optimization criterion is employed for the derivation of the optimal flow control for each of the network\u27s users. It is shown that that optimal arrival rates correspond to the unique Nash equilibrium point of a noncooperative game problem. Asynchronous algorithms are presented for the computation of the Nash equilibrium point of the network. Among them, the nonlinear Gauss-Seidel algorithms is distinguished for its robustness and speed of convergence

The Effect of Delayed Feedback Information on Network Performance

The performance of a network subject to either state dependent or state independent flow control is investigated. In the state dependent case, the flow control policy is a function of the total number of packets for which the controller has not yet received an acknowledgement. In this case it is shown that the optimal flow control is a sliding window mechanism. The effect of the delayed feedback on the network performance as well as the size of the window are studied. The state independent optimal rate is also derived. The performance of the state dependent and state independent flow control policies are compared. Conditions for employing one of the two types of flow control policies for superior end-to-end network performance are discussed. All the results obtained are demonstrated using simple examples

Decentralized Network Flow Control

In this paper, the problem of finding the decentralized flow control of a BCMP network is investigated. The packets of each of the users correspond to different classes of customers. The servers in the network are exponential and serve packets with FIFO policy. Each network user operates with either a state-dependent arrival rate (i.e. an arrival rate which depends upon the number of the user\u27s packets that have not yet been acknowledged) or a state-dependent arrival rate (which the user chooses). The decentralized flow control problem is formulated udder two optimization criteria. Under the first optimization criterion, the decentralized flow control corresponding to each of the network users maximizes the throughput of the network, under the constraint that the expected time delay of the packets in the network does not exceed a preassigned upper bound. Under the second optimization criterion, the decentralized flow control corresponding to each of the network users maximizes the throughput of the network, under the constraint that the expected time delay of each particular class of packets does not exceed a preassigned (user dependent) upper bound. In this paper all the previous classes of problems are handled uniformly, using efficient nonlinear optimization techniques

Providing mental health first aid in the workplace: a Delphi consensus study

BACKGROUND: Mental health problems are common in the workplace, but workers affected by such problems are not always well supported by managers and co-workers. Guidelines exist for the public on how to provide mental health first aid, but not specifically on how to tailor one\u27s approach if the person of concern is a co-worker or employee. A Delphi consensus study was carried out to develop guidelines on additional considerations required when offering mental health first aid in a workplace context. METHODS: A systematic search of websites, books and journal articles was conducted to develop a questionnaire with 246 items containing actions that someone may use to offer mental health first aid to a co-worker or employee. Three panels of experts from English-speaking countries were recruited (23 consumers, 26 managers and 38 workplace mental health professionals), who independently rated the items over three rounds for inclusion in the guidelines. RESULTS: The retention rate of the expert panellists across the three rounds was 61.7 %. Of the 246 items, 201 items were agreed to be important or very important by at least 80 % of panellists. These 201 endorsed items included actions on how to approach and offer support to a co-worker, and additional considerations where the person assisting is a supervisor or manager, or is assisting in crisis situations such as acute distress. CONCLUSIONS: The guidelines outline strategies for a worker to use when they are concerned about the mental health of a co-worker or employee. They will be used to inform future tailoring of Mental Health First Aid training when it is delivered in workplace settings and could influence organisational policies and procedures