3.3 Three MLE response selection paradigms
Ideally, the MLE response selection problem should be solved by a centralised operator, responsi- ble for making all of a coastal nation’s MLE response selection related decisions. Alternatively, a group of central operators should have the power to override any MLE response selection-related decisions made by less significant operators, should their decisions be considered in contravention of the fundamental MLE goals and objectives of the coastal nation. As discussed in§3.1.2, how- ever, the MLE operations of coastal nations are typically conducted by a set of semi-independent entities, each possessing their own DSSs, operators and MLE resources. The above-mentioned ideal situation may be approximated closely when these entities not only work together in perfect harmony, but also agree altogether that the purposes of certain decision entities are ultimately more important (with respect to the greater good of the coastal nation) than others. Such an altruistic situation cannot, however, realistically be expected to prevail in practice.
In this section, three paradigms for solving the MLE response selection problem are therefore proposed and described in some detail. These paradigms are:
A centralised paradigm, where a single operator dictates how decision entities should assign their MLE resources in terms of routing schedules in real time,
An intermediate paradigm, where a central operator considers the preferences of decision enti- ties to a certain extent when assessing routing schedules in real time, and
A decentralised paradigm, where a central operator shares the MLE response selection decision making process with operators of the various decision entities in the sense that the central operator represents a neutral party in charge of the VOI assignment to decision entities in real time, and the operators of the various decision entities are, in turn, in charge of establishing routing schedules with respect to the VOIs assigned to them involving their own MLE resources in real time.
It is acknowledged that, while from the collective perspective of an entire coastal nation, the first paradigm above represents an ideal scenario in terms of subsequent solution quality, the latter two paradigms represent more likely and realistic MLE response selection decision paradigms to be found in practice. But it is also acknowledged that the first two paradigms above are expected to suffer in solution quality whenever large volumes of input data have to be processed within short time frames from a central processing unit. If a coastal nation therefore does not possess a central infrastructure with strong processing power, then it may be more beneficial to split the tasks among multiple decentralised processing units, perhaps under the jurisdiction of the various decision making entities.
3.3.1 A centralised decision making paradigm
In the centralised decision making paradigm, it is envisaged that a central operator is responsible for overseeing the entire MLE response selection process of a coastal nation with the assistance of a centralised DSS. The duty of the central operator is to dictate to decision entity operators how to allocate their MLE resources to VOIs in real time. Decision entity operators therefore have no say at any point in the decision making process; their duty is merely to ensure that the operations put forward by the central operator are carried out by their respective decision entities. Decision entity operators are still required, however, to update information in the MLE database in respect of real time developments that are relevant to MLE operations assigned
to them. VOI line-of-sight observation reports or status updates in respect of the functional attributes associated with the MLE resources of an entity are other examples of the duties of decision entity operators in this paradigm. The DSS functional elements within this paradigm, together with the flow of information between them, are illustrated in Figure 3.4. In addition, the sequential order in which the functional elements operate within this MLE response selection paradigm cycle is shown in Figure 3.5.
MLE Database External Data Sources MLE Resource Assignment Infrastructure Centralised MLE Response Selection DSS MLE HMI MLE Response Selection Central Operator MLE Database Manager
Figure 3.4: Functional elements in the MLE response selection centralised decision making paradigm and the flow of information between these elements.
Trigger MLE Response Selection Subcycle Database Snapshot MLE Response Selection Database Update
Figure 3.5: The sequential order of events within the MLE response selection centralised decision making paradigm.
3.3.2 An intermediate decision making paradigm
In an intermediate decision making paradigm, the central operator may choose to consider advice, preferences and expertise from the operators of the various decision entities as to how the MLE response selection routing process should be conducted in real time. The degree of attention that the central operator affords to the opinions of decision entity operators may, however, vary from one scenario to another. Consequently, this paradigm may exist anywhere between the two
3.3. Three MLE response selection paradigms 67
extreme paradigms (the centralised paradigm described above and the decentralised paradigm proposed hereafter), possibly under different configurations. The central operator nevertheless has the final authority as to which decision alternative should be implemented.
3.3.3 A decentralised decision making paradigm
In a fully decentralised decision making paradigm, a central operator and multiple decision entity operators are together responsible for overseeing the MLE response selection process of a coastal nation. Decision entities in this paradigm are therefore afforded more decision making power with respect to the MLE response selection process.
In this paradigm it is envisaged that the central operator is responsible, with the assistance of a DSS, to oversee the so-called VOI distribution process, which consists of distributing the VOIs amongst the decision entities in real time by associating each decision entity with a specific subset of VOIs that have to be intercepted by it. Additionally, it is assumed that each decision entity has its own operator, routing DSS and MLE resources, and is independently responsible for making routing decisions involving interceptions by its own MLE resources with respect to the subset of VOIs assigned to it. Although decision entities are assumed to operate independently from one another in this paradigm and not share MLE resources, it is assumed that they share coastal nation maritime bases as well as the pre-configured patrol circuits. In this paradigm, the VOI distribution operator is therefore required to solve the VOI distribution problem, after which intercept scheduling and routing decisions are made independently by each decision entity in respect of its own MLE resources for the VOIs assigned to it.
MLE Database External Data Sources MLE Resource Assignment Infrastructure Decision Entity MLE resources Decision Entity MLE resources DSS’s VOI Distribution Decision Entities Routing Routing MLE HMI Human Operators VOI Distribution Operator Decision Entities Routing Operators MLE Database Manager
Figure 3.6: Functional elements in the MLE response selection decentralised decision making paradigm and the flow of information between these elements.
The DSS structure within this paradigm therefore consists of multiple independent operators and DSSs, each responsible for carrying out specific tasks within the MLE response selection process, overseen by a central operator. These operators are, however, assumed to have a local view in respect of their environment, only being concerned with solving their respective parts of the MLE response selection routing problem, and therefore do not need to be aware of the problem specification as a whole. The DSS functional elements within this paradigm, together with the flow of information between them, are illustrated in Figure 3.6. Additionally, the sequential order in which the functional elements function within this MLE response selection paradigm cycle is shown in Figure 3.7.
Trigger VOI Distribution Subcycle Database Snapshot VOI Distribution Database Update Trigger Routing Subcycle Database Snapshot Routes Generation Database Update Trigger Routing Subcycle Database Snapshot Routes Generation Database Update
Figure 3.7: The sequential order of events within the MLE response selection decentralised decision making paradigm.