Diversity: Cultural and biological

Early human populations utilized a wide range of biological resources in a tremendous diversity of environments. As a result, they possessed high levels of cultural diversity dependent on and supportive of high levels of biological diversity. This pattern changed drastically with technological innovations enabling certain human groups to break down territorial barriers and to usurp resources of other groups. The dominant groups have gone on to exhaust a whole range of resources, depleting both biological and cultural diversity. Traditions of resource conservation can, however, re-emerge when the dominant cultures spread over the entire area and the innovations diffuse to other human groups. This could change once again as genetically engineered organisms become an economically viable proposition with the accruing advantages concentrated in the hands of a few human groups: a further drastic reduction in biological and cultural diversity may ensue.

Cultural-Evolution of Ecological Prudence

Animals often behave in a profligate fashion and decimate the populations of plants and animals they depend upon. They may, however, evolve prudent behaviour under special conditions, namely when such prudence greatly enhances the success of populations that are not too prone to invasions by profligate individuals. Cultural evolution in human societies can also lead to the adoption of prudent practices under similar conditions. These are more likely to be realized in stable environments in which the human populations tend to grow close to the carrying capacity, when the human groups are closed, and when the technology is stagnant. These conditions probably prevailed in the hunter—gatherer societies of the tropics and subtropics, and led to the adoption of a number of socially imposed restraints on the use of plant and animal resources. Such practices were rationalized in the form of Nature-worship. The Indian caste society became so organized as to fulfill these conditions, and gave rise to two religions, Buddhism and Jainism, which emphasize compassion towards all forms of life. The pastoral nomads of the middle east, on the other hand, lived in an environment which militated against prudence, and these societies gave rise to religions like Christianity, which declared war on nature. As the ruling elite and state have grown in power, they have tried to wrest control of natural resources from the local communities. This has sometimes resulted in conservation and prudent use under guidance from the state, but has often led to conflicts with local populations to the detriment of prudent behaviour. Modern technological progress has also often removed the need for conservation, as when availability of coal permitted the deforestation of England. While modern scientific understanding has led to a better appreciation of the need for prudence, the prevailing social and economic conditions often militate against any implementation of the understanding, as is seen from the history of whaling. However, the imperative for survival of the poor from the Third-World countries may finally bring about conditions in which ecological prudence may once again come to dominate human cultures as it might once have done with stable societies of hunter—gatherers.

Efficient Energy Management Policies for Networks with Energy Harvesting Sensor Nodes

We study sensor networks with energy harvesting nodes. The generated energy at a node can be stored in a buffer. A sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time at the node. For such networks we develop efficient energy management policies. First, for a single node, we obtain policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable suboptimal policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay. Next using the results for a single node, we develop efficient MAC policies.

Average-Delay Optimal Policies for the Point-to-Point Channel

Average-delay optimal scheduflng of messages arriving to the transmitter of a point-to-point channel is considered in this paper. We consider a discrete time batch-arrival batch-service queueing model for the communication scheme, with service time that may be a function of batch size. The question of delay optimality is addressed within the semi-Markov decision-theoretic framework. Approximations to the average-delay optimal policy are obtained.

Optimized Policies for the Retransmission Probabilities in Slotted Aloha

In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability q(r) for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability qr that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. Wen also investigate the effects of using different cost functions (withn and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

Not in their genes: phenotypic flexibility, behavioural traditions and cultural evolution in wild bonnet macaques

Phenotypic flexibility, or the within-genotype, context-dependent, variation in behaviour expressed by single reproductively mature individuals during their lifetimes, often impart a selective advantage to organisms and profoundly influence their survival and reproduction. Another phenomenon apparently not under direct genetic control is behavioural inheritance whereby higher animals are able to acquire information from the behaviour of others by social learning, and, through their own modified behaviour, transmit such information between individuals and across generations. Behavioural information transfer of this nature thus represents another form of inheritance that operates in many animals in tandem with the more basic genetic system. This paper examines the impact that phenotypic flexibility, behavioural inheritance and socially transmitted cultural traditions may have in shaping the structure and dynamics of a primate society--that of the bonnet macaque (Macaca radiata), a primate species endemic to peninsular India. Three principal issues are considered: the role of phenotypic flexibility in shaping social behaviour, the occurrence of individual behavioural traits leading to the establishment of social traditions, and the appearance of cultural evolution amidst such social traditions. Although more prolonged observations are required, these initial findings suggest that phenotypic plasticity, behavioural inheritance and cultural traditions may be much more widespread among primates than have previously been assumed but may have escaped attention due to a preoccupation with genetic inheritance in zoological thinking.

Online association policies in IEEE 802.11 WLANs

In this paper, we study the performance of client-Access Point (AP) association policies in IEEE 802.11 based WLANs. In many scenarios, clients have a choice of APs with whom they can associate. We are interested in finding association policies which lead to optimal system performance. More specifically, we study the stability of different association policies as a function of the spatial distribution of arriving clients. We find for each policy the range of client arrival rates for which the system is stable. For small networks, we use Lyapunov function methods to formally establish the stability or instability of certain policies in specific scenarios. The RAT heuristic policy introduced in our prior work is shown to have very good stability properties when compared to several other natural policies. We also validate our analytical results by detailed simulation employing the IEEE 802.11 MAC.

Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Forest policies and programs affecting vulnerability and adaptation to climate change

Due to large scale afforestation programs and forest conservation legislations, India's total forest area seems to have stabilized or even increased. In spite of such efforts, forest fragmentation and degradation continues, with forests being subject to increased pressure due to anthropogenic factors. Such fragmentation and degradation is leading to the forest cover to change from very dense to moderately dense and open forest and 253 km(2) of very dense forest has been converted to moderately dense forest, open forest, scrub and non-forest (during 2005-2007). Similarly, there has been a degradation of 4,120 km(2) of moderately dense forest to open forest, scrub and non-forest resulting in a net loss of 936 km(2) of moderately dense forest. Additionally, 4,335 km(2) of open forest have degraded to scrub and non-forest. Coupled with pressure due to anthropogenic factors, climate change is likely to be an added stress on forests. Forest sector programs and policies are major factors that determine the status of forests and potentially resilience to projected impacts of climate change. An attempt is made to review the forest policies and programs and their implications for the status of forests and for vulnerability of forests to projected climate change. The study concludes that forest conservation and development policies and programs need to be oriented to incorporate climate change impacts, vulnerability and adaptation.

On the optimality of exhaustive service policies in multiclass queueing systems with modulated arrivals and switchovers

Consider a single-server multiclass queueing system with K classes where the individual queues are fed by K-correlated interrupted Poisson streams generated in the states of a K-state stationary modulating Markov chain. The service times for all the classes are drawn independently from the same distribution. There is a setup time (and/or a setup cost) incurred whenever the server switches from one queue to another. It is required to minimize the sum of discounted inventory and setup costs over an infinite horizon. We provide sufficient conditions under which exhaustive service policies are optimal. We then present some simulation results for a two-class queueing system to show that exhaustive, threshold policies outperform non-exhaustive policies.

Optimal Parameterized Policies for Resource Allocation in Communication Networks

The problem of finding optimal parameterized feedback policies for dynamic bandwidth allocation in communication networks is studied. We consider a queueing model with two queues to which traffic from different competing flows arrive. The queue length at the buffers is observed every T instants of time, on the basis of which a decision on the amount of bandwidth to be allocated to each buffer for the next T instants is made. We consider two different classes of multilevel closed-loop feedback policies for the system and use a two-timescale simultaneous perturbation stochastic approximation (SPSA) algorithm to find optimal policies within each prescribed class. We study the performance of the proposed algorithm on a numerical setting and show performance comparisons of the two optimal multilevel closedloop policies with optimal open loop policies. We observe that closed loop policies of Class B that tune parameters for both the queues and do not have the constraint that the entire bandwidth be used at each instant exhibit the best results overall as they offer greater flexibility in parameter tuning. Index Terms — Resource allocation, dynamic bandwidth allocation in communication networks, two-timescale SPSA algorithm, optimal parameterized policies. I.