A fuzzy approach for optimal placement of IoT applications in fog-cloud computing

Fog-cloud computing is a promising distributed model for hosting ever-increasing Internet of Things (IoT) applications. IoT applications should meet different characteristics such as deadline, frequency rate, and input file size. Fog nodes are heterogeneous, resource-limited devices and cannot accommodate all the IoT applications. Due to these difficulties, designing an efficient algorithm to deploy a set of IoT applications in a fog-cloud environment is very important. In this paper, a fuzzy approach is developed to classify applications based on their characteristics then an efficient heuristic algorithm is proposed to place applications on the virtualized computing resources. The proposed policy aims to provide a high quality of service for IoT users while the profit of fog service providers is maximized by minimizing resource wastage. Extensive simulation experiments are conducted to evaluate the performance of the proposed policy. Results show that the proposed policy outperforms other approaches by improving the average response time up to 13%, the percentage of deadline satisfied requests up to 12%, and the resource wastage up to 26%.

     

Effects of phenological constraints on sex allocation in cosexual monocarpic plants

The effects of two phenological constraints in resource investment to reproduction – resource limitation at the flowering stage and unpredictability of resources gained after flowering – on the resource allocation between male and female functions in monocarpic plants are considered using the ESS (evolutionarily stable strategy) approach. The model predicts that the sex allocation including the seed maturation stage has a female bias, when the quantity of reproductive resources available at flowering is small compared with that which is obtained after flowering, or when the cost of seed maturation relative to ovule production is low. The fluctuation of the quantity of resources available for seed maturation favors overproduction of ovules. As a result, more resources are allocated to female function and less to male function at flowering. The ESS allocation depends on the variability of resources and the cost of seed maturation relative to ovule production. The probability that total resource allocation has a female bias becomes higher than 0.5, and it depends on the cost of seed maturation relative to ovule production rather than resource variability. On the other hand, the probability that resource allocation has a female bias decreases with resource variability if we assume that the floral sex ratio is fixed. Future studies of plant sex allocation would profit by taking account of the phenological process of reproduction such as ovule production or seed maturation.     

Size-dependent sex allocation in hermaphroditic plants: the effects of resource pool and self-incompatibility

The effects of the resource pool and resource obtained during a season for seed maturation and self-incompatibility on the size-dependency of evolutionarily stable sex allocation were analysed theoretically. In hermaphroditic plants, reproductive resources allocated between male and female function may not be paid from a single resource pool, because plants can mature seeds using not only reserved resources but also newly gained resources after flowering. But the resource investment to male function is limited to the flowering stage. Under the assumption of constant reserve efficiency and diminishing resource return per investment to leaves, large plants should use both reserved and newly gained resources for seed maturation, while small plants should use only new resources. When both reserved and new resources are used, the optimal allocation for self-compatible species is to invest a constant amount of resources into male function irrespective of resource size, because the female fitness curve increases linearly and the male curve decelerates due to local mate competition. In self-incompatible species, on the other hand, fitness gain per investment through male function and the optimal amount of resources invested in male function decrease with size. Thus a decrease in maleness with size should be emphasized more in self-incompatible species than in self-compatible one. When only new resources are used for seed growth, the female fitness curve as well as male one decelerates with investment. Consequently, the investment in both male and female functions should increase with size, in both self-compatible and self-incompatible species. The magnitude of reserve efficiency relative to efficiency of resource gain after flowering affects size-dependent pattern of sex allocation, while the cost of seed maturation relative to ovule production has little effect on it. The plant size variation in a population emphasizes size-dependency of sex allocation. When size variation is large enough, it is possible that large plants become complete female in self-incompatible species, but it is not in self-compatible species.     

VRAA: virtualized resource auction and allocation based on incentive and penalty

Virtualization is widely used in cloud computing environments to efficiently manage resources, but it also raises several challenges. One of them is the fairness issue of resource allocation among virtual machines. Traditional virtualized resource allocation approaches distribute physical resources equally without taking into account the actual workload of each virtual machine and thus often leads to wasting. In this paper, we propose a virtualized resource auction and allocation model (VRAA) based on incentive and penalty to correct this wasting problem. In our approach, we use Nash equilibrium of cooperative games to fairly allocate resources among multiple virtual machines to maximize revenue of the system. To illustrate the effectiveness of the proposed approach, we then apply the basic laws of auction gaming to investigate how CPU allocation and contention can affect applications’ performance (i.e., response time), and its effect on CPU utilization. We find that in our VRAA model, the fairness index is high, and the resource allocation is closely proportional to the actual workloads of the virtual machines, so the wasting of resources is reduced. Experiment results show that our model is general, and can be applied to other virtualized non-CPU resources.     

Resource scheduling methods in cloud and fog computing environments: a systematic literature review

In recent years, cloud computing can be considered an emerging technology that can share resources with users. Because cloud computing is on-demand, efficient use of resources such as memory, processors, bandwidth, etc., is a big challenge. Despite the advantages of cloud computing, sometimes it is not a proper choice due to its delay in responding appropriately to existing requests, which led to the need for another technology called fog computing. Fog computing reduces traffic and time lags by expanding cloud services to the network and closer to users. It can schedule resources with higher efficiency and utilize them to impact the user's experience dramatically. This paper aims to survey some studies that have been done in the field of scheduling in fog/cloud computing environments. The focus of this survey is on published studies between 2015 and 2021 in journals or conferences. We selected 71 studies in a systematic literature review (SLR) from four major scientific databases based on their relation to our paper. We classified these studies into five categories based on their traced parameters and their focus area. This classification comprises 1—performance 2—energy efficiency, 3—resource utilization, 4—performance and energy efficiency, and 5—performance and resource utilization simultaneously. 42.3% of the studies focused on performance, 9.9% on energy efficiency, 7.0% on resource utilization, 21.1% on both performance and energy efficiency, and 19.7% on both performance and resource utilization. Finally, we present challenges and open issues in the resource scheduling methods in fog/cloud computing environments.

     

Matchmaking: An extensible framework for distributed resource management

Federated distributed systems present new challenges to resource management. Conventional resource managers are based on a relatively static resource model and a centralized allocator that assigns resources to customers. Distributed environments, particularly those built to support high-throughput computing (HTC), are often characterized by distributed management and distributed ownership. Distributed management introduces resource heterogeneity: Not only the set of available resources, but even the set of resource types is constantly changing. Distributed ownership introduces policy heterogeneity: Each resource may have its own idiosyncratic allocation policy. To address these problems, we designed and implemented the Matchmaking resource management framework. Customers and resources are all described by classified advertisements (classads) written in a simple but powerful formal language that describes their attributes and allocation policies. A Matchmaker server uses a policy-independent matching operation to discover pairings. It notifies the parties to the match, which use a separate, bilateral claiming protocol to confirm the allocation. The resulting framework is robust, scalable and flexible, and can evolve with changing resources. Matchmaking is the core of the Condor High Throughput Computing System developed at the University of Wisconsin — Madison. Condor is a production-quality system used by scientists and engineers at sites around the world. Condor derives much of its flexibility, robustness and efficiency from the matchmaking architecture. We describe the use of matchmaking in Condor, presenting several examples that illustrate its flexibility and expressiveness. This revised version was published online in July 2006 with corrections to the Cover Date.     

Seasonal Allocation and Efficiency Patterns of Biomass and Resources in the Perennial Geophyte Sparaxis grandiflora Subspecies fimbriata (Iridaceae) in Lowland Coastal Fynbos, South Africa

The seasonal allocation and efficiency of biomass and resources(starch, soluble carbohydrates, N, P, K, Ca, Mg, Na, Zn, Fe,Mn and Cu) within and between the constituent plant parts ofSparaxis grandiflora subspecies fimbriata , a deciduous, synanthousgeophyte, are described. The sequential production of roots,leaves and a new daughter corm, with fruit production phasedin during the development of the daughter corm, results in continualtransfer of resources when the plant is not dormant. The newdaughter corm serves as the major sink for the allocation ofdry matter and resources during the vegetative, reproductiveand senescent periods. The parent corm is the major source ofresources in the early stages of the vegetative period. Theamount of resources allocated to the reproductive structureswas comparatively low when compared with that allocated to vegetativeplant parts. The corms have highly flexible storage capacitiesfor a variety of nutrients, particularly the better conservednutrients such as nitrogen, phosphorus, potassium, and carbohydrates.The dynamic patterns for the majority of the resources revealedhigh allocation when metabolic activity was also highest. Efficientrecovery or recycling of important resources from senescingorgans results in a similar or greater allocation to the daughtercorm than the amount that was present in the parent corm ofthe previous growth season. This is seen as an advantage tothese plants that grow in a seasonal environment where soilsare of low nutrient status.Copyright 1994, 1999 Academic Press Dry mass, efficiency, phenophase, resource allocation, Sparaxis grandiflora, fynbos     

DOES THE TRADE-OFF BETWEEN GROWTH AND REPRODUCTION SELECT FOR FEMALE-BIASED SEXUAL ALLOCATION IN COSEXUAL PLANTS?

We analyzed sexual allocation in cosexual plants while taking the trade-off between growth and reproduction into consideration and showed that this trade-off does not select for female-biased sexual allocation. There are two problems in sexual allocation: optimizing the amount of resources allocated to reproduction in a growing season and equalizing the resources allocated to the male and the female functions. If these two are possible at the same time, equal resource allocation to the male and the female functions is the evolutionarily stable strategy (ESS; given that the fitness gains through the male and the female functions are proportional to the amount of the resources allocated to these functions). Biased sexual allocation only occurs when constraints make it impossible to simultaneously optimize allocation to reproduction and allocation to male and female functions. However, even if female-biased sexual allocation occurs due to the addition of other constraints, the trade-off between growth and reproduction itself is not an important factor that selects for female-biased sexual allocation.     

Allocation from capital and income sources to reproduction shift from first to second clutch in the flesh fly, Sarcophaga crassipalpis

Understanding how resources are allocated between survival and reproduction is fundamental to the study of the evolution of life histories. Reproductive resources can come from two intrinsic resource pools, stored reserves (capital) acquired before reproduction or income acquired during reproduction. The variety of reproductive strategies in insects is remarkable and reproductive allocation encompasses the complete range of allocation strategies from pure capital breeders to pure income breeders. However, most organisms probably use a blend of capital and income and this blend is likely dynamic, changing between reproductive bouts in response to internal and external conditions. We used stable isotopes to quantify the allocation of capital and income resources to reproduction in the flesh fly, Sarcopha crassipalpis and assessed how allocation patterns change over multiple bouts of reproduction. Sarcophaga crassipalpis shifts from a slight investment of capital in the first clutch to an almost pure income breeder in the second clutch. We discuss the relationship between activity and allocation, and the potential for this system to understand how allocation patterns change in response to environmental stress.     

Carbon allocation and competition maintain variation in plant root mutualisms

Plants engage in multiple root symbioses that offer varying degrees of benefit. We asked how variation in partner quality persists using a resource‐ratio model of population growth. We considered the plant's ability to preferentially allocate carbon to mutualists and competition for plant carbon between mutualist and nonmutualist symbionts. We treated carbon as two nutritionally interchangeable, but temporally separated, resources—carbon allocated indiscriminately for the construction of the symbiosis, and carbon preferentially allocated to the mutualist after symbiosis establishment and assessment. This approach demonstrated that coexistence of mutualists and nonmutualists is possible when fidelity of the plant to the mutualist and the cost of mutualism mediate resource competition. Furthermore, it allowed us to trace symbiont population dynamics given varying degrees of carbon allocation. Specifically, coexistence occurs at intermediate levels of preferential allocation. Our findings are consistent with previous empirical studies as well the application of biological market theory to plantroot symbioses.     

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical modeling.     

Toward an allocation scheme for global terrestrial carbon models

The distribution of assimilated carbon among the plant parts has a profound effect on plant growth, and at a larger scale, on terrestrial biogeochemistry. Although important progress has been made in modelling photosynthesis, less effort has been spent on understanding the carbon allocation, especially at large spatial scales. Whereas several individual-level models of plant growth include an allocation scheme, most global terrestrial models still assume constant allocation of net primary production (NPP) among plant parts, without any environmental coupling. Here, we use the CASA biosphere model as a platform for exploring a new global allocation scheme that estimates allocation of photosynthesis products among leaves, stems, and roots depending on resource availability. The philosophy underlying the model is that allocation patterns result from evolved responses that adjust carbon investments to facilitate capture of the most limiting resources, i.e. light, water, and mineral nitrogen. In addition, we allow allocation of NPP to vary in response to changes in atmospheric CO₂. The relative magnitudes of changes in NPP and resource-use efficiency control the response of root:shoot allocation. For ambient CO₂, the model produces realistic changes in above-ground allocation along productivity gradients. In comparison to the CASA standard estimate using fixed allocation ratios, the new allocation scheme tends to favour root allocation, leading to a 10% lower global biomass. Elevated CO₂, which alters the balance between growth and available resources, generally leads to reduced water stress and consequently, decreased root:shoot ratio. The major exception is forest ecosystems, where increased nitrogen stress induces a larger root allocation.     

A life history model of somatic damage associated with resource acquisition: damage protection or prevention?

A resource acquisition-allocation model is developed to examine the trade-off between reproduction and somatic protection. Unlike previous studies, resource intake is not assumed to be constrained: instead, resource intake is free to vary, with increased intake being associated with an increased risk of somatic damage. This gives rise to an optimal resource intake as well as an optimal allocation strategy. This paper studies the relative importance of acquisition and allocation strategies in regulating acquisition-related mortality. Under the optimal allocation strategy mortality rate increases with age, in accordance with the disposable soma theory of aging. Contrary to the usual interpretation of the disposable soma theory, this increase in mortality can arise from an increase in the resource acquisition effort rather than a decrease in the resources allocated to protection. At early ages resource acquisition is found to be the primary path for regulating life history costs, whilst allocating resources to protection becomes more important later in life. Models for targeted and non-targeted damage repair are considered and the robustness of our results to the structure and parameterization of the model is discussed. The results from our models are discussed in light of published data. Resource acquisition is shown to be a potentially important mechanism for controlling somatic damage which deserves further study.     

The costs of crest induction for Daphnia carinata

The effects of notonectid-induced crests on growth and reproduction, and resource allocation to crest construction, moult losses and eggs of Daphnia carinata were measured. An attempt was made to elucidate the mechanisms of physiological costs of crest induction for this species. The crested morph of d. carinata reached a significantly larger size than the uncrested form. Reproductive output was similar in early instars, but the crested morph produced more eggs in latter broods. Instar duration was longer for the crested morph and age at first reproduction was delayed. Survival was also lower in this form. Crest construction required significant resources (equivalent to 60 eggs over a life time) but evidence is presented that these resources were obtained primarily by re-allocation of available material rather than collection of extra resources. The crested morph allocated significantly more resources to moulting than its uncrested counter-parts. The uncrested morph produced large eggs in early instars and progressively smaller ones in later instars. The crested morph produced only small eggs. The hypothesis is presented that the crest-induction strategy of D. carinata involves at least two separate sets of responses, each with its own costs and trade-offs. The first response is production of the crest. The cost of crest production is an increased cost of moulting. D. carinata off sets this cost by increasing instar duration and thus age at reproduction. The second response is increased size. D. carinata achieves this by reducing the fraction of available resources allocated to reproduction. The cost is lower reproductive output.     

Enhanced immune function does not depress reproductive output

Costs of reproduction might be mediated by a physiological (resource allocation) trade-off between immune function and reproductive effort, and several recent studies have shown that an experimental increase in reproductive effort is associated with decreased immune function. Here we test the complementary prediction of this hypothesis: that increased immune function (specific antibody production) depresses reproductive output. Female European starlings (Sturnus vulgaris) were injected with a non-pathogenic antigen (sheep red blood cells) following completion of laying of their first clutch, to stimulate an in vivo humoral immune response (primary antibody production). We induced laying of a second clutch by removing the first clutch, and assessed changes in reproductive performance in individual females pre- and post-treatment. Injection of sheep red blood cells produced a significant antibody response in 96% (n=29) of treated females, with titres comparable to previous studies (range 1 to 7). However, increased antibody production did not decrease primary or secondary female reproductive effort (re-laying interval, egg size, clutch size, chick growth or fledging success), compared with control, saline-injected birds (n=22). These data do not support a simple resource allocation model for the cost of reproduction, based on a reciprocal, negative relationship between resources allocated to immune function and reproduction.     

Autonomic resource management in virtualized data centers using fuzzy logic-based approaches

Data centers, as resource providers, are expected to deliver on performance guarantees while optimizing resource utilization to reduce cost. Virtualization techniques provide the opportunity of consolidating multiple separately managed containers of virtual resources on underutilized physical servers. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared physical resources to virtual containers and the management of their capacities to meet service-quality targets at the least cost. This paper proposes a two-level resource management system to dynamically allocate resources to individual virtual containers. It uses local controllers at the virtual-container level and a global controller at the resource-pool level. An important advantage of this two-level control architecture is that it allows independent controller designs for separately optimizing the performance of applications and the use of resources. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the local controller designs is their use of fuzzy logic-based approaches to efficiently and robustly deal with the complexity and uncertainties of dynamically changing workloads and resource usage. The global controller determines the resource allocation based on a proposed profit model, with the goal of maximizing the total profit of the data center. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.

Patterns of biomass allocation to male and female functions in plants with different mating systems

Summary Using dry weight biomass we examined the patterns of investment in male and female functions (prezygotic cost) in plants with different mating systems. All the flower parts of both xenogamous and facultatively xenogamous species were heavier, i.e., larger, than those of facultatively autogamous species. Likewise, the dry weights of all the flower parts of xenogamous species exceeded those of facultatively xenogamous species. On a relative basis, xenogamous species invested less in calyces and more in corollas compared to species with the other mating systems. Facultatively autogamous species invested relatively more in pistils. Xenogamous species invested relatively more in stamens than do facultatively autogamous species. The ratios of dry weight stamens to dry weight pistils were equivalent in xenogamous and facultatively xenogamous species.The available data from xenogamous species suggest a pattern of resource allocation that is independent of sexual system (perfect-flowered, monoecious, or dioecious) and pollen vector. The cost of mating (prezygotic cost) was male biased and frequently exceeded by parental investment (postzygotic cost). These results are not consistent with models that predict equal allocation of resources to male and female sexual function but are consistent with those that predict unequal allocation of resources to those functions in outbreeding hermaphroditic angiosperms. Two additional lines of evidence are inconsistent with the expectations of sex allocation theory. First, resource allocation to sexual function was not equal in wind-pollinated species. Second, relative amounts of the resources allocated to male vis-à-vis female function did not decrease between xenogamy and facultative xenogamy i.e., with an increase in the selfing rate.     

Plant reproductive allocation predicts herbivore dynamics across spatial and temporal scales

Life-history theory suggests that iteroparous plants should be flexible in their allocation of resources toward growth and reproduction. Such plasticity could have consequences for herbivores that prefer or specialize on vegetative versus reproductive structures. To test this prediction, we studied the response of the cactus bug (Narnia pallidicornis) to meristem allocation by tree cholla cactus (Opuntia imbricata). We evaluated the explanatory power of demographic models that incorporated variation in cactus relative reproductive effort (RRE; the proportion of meristems allocated toward reproduction). Field data provided strong support for a single model that defined herbivore fecundity as a time-varying, increasing function of host RRE. High-RRE plants were predicted to support larger insect populations, and this effect was strongest late in the season. Independent field data provided strong support for these qualitative predictions and suggested that plant allocation effects extend across temporal and spatial scales. Specifically, late-season insect abundance was positively associated with interannual changes in cactus RRE over 3 years. Spatial variation in insect abundance was correlated with variation in RRE among five cactus populations across New Mexico. We conclude that plant allocation can be a critical component of resource quality for insect herbivores and, thus, an important mechanism underlying variation in herbivore abundance across time and space.     

Trust management for internet of things using cloud computing and security in smart cities

Many consumers participate in the smart city via smart portable gadgets such as wearables, personal gadgets, mobile devices, or sensor systems. In the edge computation systems of IoT in the smart city, the fundamental difficulty of the sensor is to pick reliable participants. Since not all smart IoT gadgets are dedicated, certain intelligent IoT gadgets might destroy the networks or services deliberately and degrade the customer experience. A trust-based internet of things (TM-IoT) cloud computing method is proposed in this research. The problem is solved by choosing trustworthy partners to enhance the quality services of the IoT edging network in the Smart architectures. A smart device choice recommendation method based on the changing networks was developed. It applied the evolutionary concept of games to examine the reliability and durability of the technique of trust management presented in this article. The reliability and durability of the trustworthiness-managing system, the Lyapunov concept was applied.A real scenario for personal-health-control systems and air-qualitymonitoring and assessment in a smart city setting confirmed the efficiency of the confidence-management mechanism. Experiments have demonstrated that the methodology for trust administration suggested in this research plays a major part in promoting multi-intelligent gadget collaboration in the IoT edge computer system with an efficiency of 97%. It resists harmful threads against service suppliers more consistently and is ideal for the smart world's massive IoT edge computer system.

     

Energy allocation strategy modifies growth–survival trade-offs in juvenile fish across ecological and environmental gradients

In young temperate zone fishes, conflicting energy demands lead to variability in growing season and winter survival. Growing season survival is driven by size-dependent predation risk whereas winter survival is constrained by autumn body size, energy storage and winter duration. We developed a model of the seasonality of energetics coupled to empirical measures of resource availability, size-dependent predation and temperature seasonality for rainbow trout (Oncorhynchus mykiss) in two sets of lakes in British Columbia, Canada, representing endpoints of a gradient of temperature, growing season duration and winter duration. This model was used to determine the energy allocation strategy which maximized first-year survival across these gradients. Survival was sensitive to the timing of the switch from somatic to storage strategies in cold, short growing season, low resource environments. A broader range of energy allocation strategies were viable in warmer, longer growing season and higher resource lakes. We used empirical observations of autumn energy storage and our modeled values for size-dependent minimal lipid levels needed to survive winter in each system to estimate winter survival for juvenile rainbow trout. Winter survival estimates were 6% in cold lakes with low resources, 82% in warm, lakes with low resources and 100% in warm lakes with high resources. Fish in warm lakes with ample resources allocated substantially more to storage than the minimum required to survive winter generated from our model, suggesting additional selection pressures for increased storage when there was ample surplus energy. We concluded that growth–survival trade-offs, modified by seasonality of the environment, influenced the growing season energy allocation strategies for young-of-the-year fish, and suggested this may be important for understanding population viability across environmental gradients.