Auction Mechanisms in Cloud/Fog Computing Resource Allocation for Public Blockchain Networks

As an emerging decentralized secure data management platform, blockchain has gained much popularity recently. To maintain a canonical state of blockchain data record, proof-of-work based consensus protocols provide the nodes, referred to as miners, in the network with incentives for confirming new block of transactions through a process of "block mining" by solving a cryptographic puzzle. Under the circumstance of limited local computing resources, e.g., mobile devices, it is natural for rational miners, i.e., consensus nodes, to offload computational tasks for proof of work to the cloud/fog computing servers. Therefore, we focus on the trading between the cloud/fog computing service provider and miners, and propose an auction-based market model for efficient computing resource allocation. In particular, we consider a proof-of-work based blockchain network. Due to the competition among miners in the blockchain network, the allocative externalities are particularly taken into account when designing the auction mechanisms. Specifically, we consider two bidding schemes: the constant-demand scheme where each miner bids for a fixed quantity of resources, and the multi-demand scheme where the miners can submit their preferable demands and bids. For the constant-demand bidding scheme, we propose an auction mechanism that achieves optimal social welfare. In the multi-demand bidding scheme, the social welfare maximization problem is NP-hard. Therefore, we design an approximate algorithm which guarantees the truthfulness, individual rationality and computational efficiency. Through extensive simulations, we show that our proposed auction mechanisms with the two bidding schemes can efficiently maximize the social welfare of the blockchain network and provide effective strategies for the cloud/fog computing service provider.Comment: 15 page

Pareto-Optimal Allocation of Transactive Energy at Market Equilibrium in Distribution Systems: A Constrained Vector Optimization Approach

In a grid constrained transactive distribution system market, distribution locational marginal pricing DLMP is influenced by the distance from the substation to an energy user, thereby causing households that are further away from the substation to be charged more. The Jain index of fairness, which has been recently applied to alleviate this undesirable effect of inefficient energy allocations, is used in this research to quantify fairness. It is shown that the Jain index is strictly quasi-concave. A bilevel distributed mechanism is proposed, where at the lower level, auction mechanisms are invoked simultaneously at each aggregator to obtain energy costs under market equilibrium conditions. A constrained multi gradient ascent algorithm, Augmented Lagrangian Multigradient Approach ALMA, is proposed for implementation at the upper level to attain energy allocations that represent tradeoffs between efficiency and fairness. Theoretical issues pertaining to ALMA as a generic algorithm for constrained vector optimization are considered. It is shown that when the objectives are restricted to be strictly quasi concave functions and if the feasible region is convex, ALMA converges towards global Pareto optimality. The overall effectiveness of the proposed approach is confirmed through a set of MATLAB simulations implemented on a modified IEEE 37-bus system platform

Mathematical Frameworks for Pricing in the Cloud: Revenue, Fairness, and Resource Allocations

As more and more users begin to use the cloud for their computing needs, datacenter operators are increasingly pressed to effectively allocate their resources among these client users. Yet while much work has been done in this area, relatively little attention has been paid to studying perhaps the ultimate lever of resource allocation: pricing. Most data centers today charge users by "bundling" heterogeneous resources together in a fixed ratio and selling these bundles to their clients. But bundling masks the fact that different users require different combinations of resources (e.g., CPUs, memory, bandwidth) to process their jobs. The presence of multiple resources in fact allows an operator to offer many different types of pricing strategies, which may have different effects on its revenue. Moreover, to avoid user dissatisfaction, operators must consider the impact of their chosen prices on the fairness of the jobs processed for different users. In this paper, we develop an analytical framework that accounts for the fairness and revenue tradeoffs that arise in a datacenter's multi-resource setting and the impact that different pricing plans can have on this tradeoff. We characterize the implications of different pricing plans on various fairness metrics and derive analytical limits on the operator's fairness-revenue tradeoff. We then provide an algorithm to navigate this tradeoff and compare the tradeoff points for different pricing strategies on a data trace taken from a Google cluster

Shared Spectrum Access Communications: A Neutral Host Micro Operator Approach

In this paper, we conceive an advanced neutral host micro operator (NH-{\mu}O) network approach providing venues with services tailored to their specialized/specific requirements and/or local context related services that the mobile network operators (MNOs) are poorly-suited to providing it, as well as mobile broadband experience to the users from MNOs in a venue where only a single infrastructure is mandated under shared spectrum access framework. A radio access network slicing concept is conceived to support and optimize both the slice instance (SI) use cases independently and efficiently by running all network implementations in parallel, simultaneously on a common physical network infrastructure. We devise a common shared architecture for the NH-{\mu}O small cell base stations and dynamic spectrum assignment control unit, and their required functionalities supporting coexistence of different SIs as well as multiple MNOs in shared spectrum access communications. We devise both inter-SI and intra- SI dynamic spectrum allocation policies considering time-varying requirements of different SIs. The policies are capable of taking care of application level priority, -i.e., mixture of guaranteed quality of service and best-effort service users served by each SI while ensuring a healthy competition. Our proposed framework serves two-fold advantages, such as it gives the venue owner its own managed wireless networks tailored to its very specific requirements, and it also brings out cost savings and coverage extension for MNOs and efficiency of resources that arise from sharing wireless networks, and delivering the network capacity into high density venues

Multi-resource Energy-efficient Routing in Cloud Data Centers with Networks-as-a-Service

With the rapid development of software defined networking and network function virtualization, researchers have proposed a new cloud networking model called Network-as-a-Service (NaaS) which enables both in-network packet processing and application-specific network control. In this paper, we revisit the problem of achieving network energy efficiency in data centers and identify some new optimization challenges under the NaaS model. Particularly, we extend the energy-efficient routing optimization from single-resource to multi-resource settings. We characterize the problem through a detailed model and provide a formal problem definition. Due to the high complexity of direct solutions, we propose a greedy routing scheme to approximate the optimum, where flows are selected progressively to exhaust residual capacities of active nodes, and routing paths are assigned based on the distributions of both node residual capacities and flow demands. By leveraging the structural regularity of data center networks, we also provide a fast topology-aware heuristic method based on hierarchically solving a series of vector bin packing instances. Our simulations show that the proposed routing scheme can achieve significant gain on energy savings and the topology-aware heuristic can produce comparably good results while reducing the computation time to a large extent.Comment: 9 page

Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network

Future wireless networks will progressively displace service provisioning towards the edge to accommodate increasing growth in traffic. This paradigm shift calls for smart policies to efficiently share network resources and ensure service delivery. In this paper, we consider a cognitive dynamic network architecture (CDNA) where primary users (PUs) are rewarded for sharing their connectivities and acting as access points for secondary users (SUs). CDNA creates opportunities for capacity increase by network-wide harvesting of unused data plans and spectrum from different operators. Different policies for data and spectrum trading are presented based on centralized, hybrid and distributed schemes involving primary operator (PO), secondary operator (SO) and their respective end users. In these schemes, PO and SO progressively delegate trading to their end users and adopt more flexible cooperation agreements to reduce computational time and track available resources dynamically. A novel matching-with-pricing algorithm is presented to enable self-organized SU-PU associations, channel allocation and pricing for data and spectrum with low computational complexity. Since connectivity is provided by the actual users, the success of the underlying collaborative market relies on the trustworthiness of the connections. A behavioral-based access control mechanism is developed to incentivize/penalize honest/dishonest behavior and create a trusted collaborative network. Numerical results show that the computational time of the hybrid scheme is one order of magnitude faster than the benchmark centralized scheme and that the matching algorithm reconfigures the network up to three orders of magnitude faster than in the centralized scheme.Comment: 15 pages, 12 figures. A version of this paper has been published in IEEE/ACM Transactions on Networking, 201

Incentive-compatible route coordination of crowdsourced resources

Technical ReportWith the recent trend in crowdsourcing, i.e., using the power of crowds to assist in satisfying demand, the pool of resources suitable for GeoPresen-ce-capable systems has expanded to include already roaming devices, such as mobile phones, and moving vehicles. We envision an environment, in which the motion of these crowdsourced mobile resources is coordinated, according to their preexisting schedules to satisfy geo-temporal demand on a mobility field. In this paper, we propose an incentive compatible route coordination mechanism for crowdsourced resources, in which participating mobile agents satisfy geo-temporal requests in return for monetary rewards. We define the Flexible Route Coordination (FRC) problem, in which an agent’s flexibility is exploited to maximize the coverage of a mobility field, with an objective to maximize the revenue collected from satisfied paying requests. Given that the FRC problem is NP-hard, we define an optimal algorithm to plan the route of a single agent on a graph with evolving labels, then we use that algorithm to define a 1-approximation algorithm to solve the 2 problem in its general model, with multiple agents. Moreover, we define an incentive compatible, rational, and cash-positive payment mechanism, which guarantees that an agent’s truthfulness about its flexibility is an ex-post Nash equilibrium strategy. Finally, we analyze the proposed mechanisms theoretically, and evaluate their performance experimentally using real mobility traces from urban environments

Throughput and Energy-Efficient Network Slicing

Network slicing allows 5G network operators to provide service to multiple tenants with diverging service requirements. This paper considers network slicing aware optimal resource allocation in terms of throughput and energy efficiency. We define a heterogeneous Quality of Service (QoS) framework for a sliced radio access network network with per-slice zero-forcing beamforming and jointly optimize power and bandwidth allocation across slices and users. The Pareto boundary of this multi-objective optimization problem is obtained by two different algorithms based on the utility profile and scalarization approaches combined with generalized fractional programming. Numerical results show the merits of jointly allocating bandwidth and transmission power and how throughput and global energy efficiency are influenced by slice specific QoS requirements.Comment: Presented at International ITG Workshop on Smart Antennas (WSA) Bochum, German

Aggregate cost implications of selected Cost-Drivers \ud in the Tanzanian Health Sector\ud

\ud Health is an important aspect of life of which one of its determinants is healthcare which is consumed in order to restore back deteriorated health to optimal pre-illness levels. The consumption of healthcare however has cost implications and accounts for a large share of resources directed towards the health sector. In health sector financing, it is vital to identify major cost components and create awareness about the costs of decisions. It is thus vital to identify factors that can cause changes in the cost of identified activities. A number of costly programs have been initiated and some others are on the horizon. In order to create awareness about the financial consequences of these decisions and to draw attention to the financing needs of the health sector, it is considered necessary to analyze the major health sector programs and initiatives with regard to the changes in costs brought about by new strategies, guidelines and interventions (including the adoption of new technologies), and aggregate these costs. The main objective of this study was to identify cost-driving decisions in the health sector. The study methodology comprised of three independent but complementary methodologies and activities: (a) Desk review of literature and documents; (b) Interviews with officials from MOHSW, programs and agencies involved in setting and promoting standards at international level; (c) collection of primary data/information and subsequent analysis of the same. The study reviewed 11 plans, including summary plans like the Health Sector Strategic Plan III and the Primary Health Services Development Program 2007 -2017 and national disease control programme plans/strategies. However, not all of cost-driving decisions in these plans could be integrated into the analysis because the plans are undergoing reprogramming, as the previous cost estimates are regarded not to be realistic relative to achieving plan objectives. In addition the costs of some decisions in some plans/strategies HRH, infrastructure, health care financing strategy, mhealth, etc. are not established or are in the process of being costed or reviewed. It should also be noted that the consultants did not assess all plans/strategies and their associated costs as to their plausibility. This was neither task of the consultants, nor would the time allocated to the study have allowed such an in-depth review. The study reviewed a total of 11 multi-year plans/strategies and found four plans to be affected by costs of decisions. Such decisions are: the adaption of WHO recommendations on Anti-retroviral Treatment eligibility criteria; re-treatment of conventional nets; indoor residual spraying; sustaining availability of long lasting insecticide treated nets (LLINs); provision of delivery kits to pregnant women in public health facilities, and the potential future introduction of a malaria vaccine, human papilloma virus and pneumococcal vaccines, which affect the Health Sector HIV and AIDS Strategic Plan II (HSHSP II) 2008 – 2012, the Malaria Mid-Term Strategic Plan 2008 – 2013 (NMCP), the National Road Map Strategic Plan to Accelerate Reduction of Maternal, Newborn and Child Deaths in Tanzania 2008 – 2015 (the Road Map), and the Expanded Program on Immunization 2010 - 2015 Comprehensive Multi Year Plan (EPI), respectively. The study found that these decisions have a significant cost implication to a tune of US$706,688,405 over a five year period 2011- 2015. The initially estimated costs of programs that are currently being updated (HSHSP II, EPI, NMCP and the Road Map) is US$ 2,297,009,378 exclusive of the identified cost drivers. The estimated cost of decisions is about 8 % of the total costs for health sector in Tanzania (HSSP III estimate) and about 3.3% of the 2009 GDP and added nominal per capita health spending/cost of US$17.3 (2009 population estimate) for five year period (annual per capita cost of US$ 3.46). This expenditure will definitely boost per capita health spending (US$13.45 in 2008/9). However, concerted revenue effort is needed if we are to hit HSSP III target of US$ 26.6 in 2014/15. The National Strategy for Non-communicable Diseases 2009 – 2015 did not include estimates, while most parts of the National Road Map Strategic Plan to Accelerate Reduction of Maternal, Newborn and Child Deaths in Tanzania 2008 – 2015 are undergoing reprogramming, as the previous cost estimates are regarded not to be realistic relative to achieving plan objectives. The rest of the programs are not significantly affected by cost of decisions. However, the estimated cost is likely to be higher owing to the fact that costs of some decisions in MMAM components such as HRH, infrastructure, health care financing strategy, mhealth, etc. are not established or are in the process of being costed or reviewed. Prevention and treatment of illness are the major strategies used to maintain or improve the health status of a population. Allocation of health resources are usually skewed towards treatment probably because addressing existing illnesses seem a present and clear danger than addressing potential illnesses which is what prevention is all about. Prevention and health promotion however lead to greater benefits than treatment in the long run in the sense that it reduces future demand for treatment than treatment alone does and has stronger merit good characteristics than treatment of illness. Health planning should thus intensify focus on prevention through promoting lifestyle and behaviour changes as well as intensifying prevention and health promotion at community level. Most health sector multi-year plans are characterized by heavy resource dependence on development partners. Such levels of dependence tend to compromise control over some decisions especially those supported by financiers. That is, recipients may be tempted to accept a full funded activity even if there is an ongoing similar activity which ends up creating parallel rather than complementary activities with cost implications. Thus, the financiers and recipients should undertake thorough analysis of potential decisions based on their cost implications (direct and indirect) as well as the time parameters, while avoiding decisions that spin off similar activities rather than complementing the existing ones. This can be facilitated by coordinated analysis from the MOHSW by keeping and monitoring comprehensive cost driver table enriched by inputs from all health sector programs and plans. Continuous reviews of the plans enhance the capacity of programs to adequately identify cost drivers and therefore enhance the planning process. However, reviews are not always undertaken on time and as regular as possible due to lack of resources or transfer of resources set aside for review process to implement other pressing components of the plan. MOHSW should make costing part of the plan a compulsory exercise for approval by the management and should not endorse plans which have not been adequately costed. MOHSW should also consider making reviews of multi-year plans a prerequisite for release of fund for subsequent implementation. Moreover, the reviews should integrate all stakeholders and involve technical people who are knowledgeable in costing and planning. The fact that most of the multi-year plans had indicative budgets, while others are not costed at all, warrants the conclusion that the basic knowledge in costing such as collaboration, parameter assumptions, time, manpower, and resources is lacking. Emphasis should thus be placed on developing and improving costing capacity in the programs as well as the MOHSW in terms of acquiring costing tools and exposure. The MOHSW should ensure that the priority activities of the strategies/plans are funded. This could be done through lobbying the government and other stakeholders for more resources. Protocols such as Abuja Declaration 2001, in which African governments committed themselves to scale up health budget to 15% of the annual budget, could be useful in this end. Also the government and local authorities through laws/bylaws could establish and commit specific sources of resources for the health sector. This should be pursued by keeping a close eye on the ratio of available resources to required resources which can indicate opportunities which development partners can be of help as well as providing an indication of the realism of planning. A review of the plans found the ratio of available resources to required resources to be 76 and 84 percent, respectively, for the Health Sector Strategic Plan III and the Expanded Program on Immunization 2010 – 2015 Comprehensive Multi Year Plan. The Malaria Medium Term Strategic Plan 2008-2013 on the other hand had the lowest ratio of available resources to required resources of 35 percent.\u

Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making